We are looking for Associate Principal AI Data Scientists eager to utilise their expertise in these advanced technologies to revolutionise our drug development processes. In the Pharmaceutical Technology and Development (PT&D) department, you will be a key player in transforming molecules into groundbreaking medical treatments.

Your role involves contributing data science expertise into cross-functional global pharmaceutical development projects in support of transforming the way we deliver medicines to patients. You'll play a pivotal role in shaping our AI strategy and driving the co-development of sophisticated HITL multi-agent systems.

We are hiring two candidates for this position, and the roles will be based at our dynamic site in Durham (USA).

Work Modality: Hybrid (3 days office and 2 remote)

Accountabilities:

• Drive innovation in agentic AI, multi-agent systems, and digital twins, exploring new methodologies and applications.

• Design, implement, and optimise algorithms for autonomous decision-making, coordination, and policy learning among agents and digital twins using techniques like Markov Decision Processes (MDPs), Partially Observable MDPs (POMDPs), and multi-agent reinforcement learning (MARL).

• Evaluate agent performance in the context of decision making, collaboration, competition, uncertainty.

• Collaborate with cross-functional teams ensuring knowledge transfer to IT engineering teams for IT solution builds and deployment.

• Keep pace with industry advancements by reviewing academic papers and attending conferences. Publish findings in peer-reviewed journals and represent the company at scientific forums.

• Communicate technical concepts and results to technical and non-technical audiences.

Essential skills/Experience:

• Min Bachelor's degree in computer science, data science, artificial intelligence, machine learning or related fields.

• At least 3 years of experience in Deep Learning and ML.

• Excellent coding skills in languages such as Python, R.

• Hands-on industrial experience designing multi-agent patterns, digital twins and experience with agentic AI design patterns, reinforcement learning.

• Extensive industrial experience with AI and ML frameworks like TensorFlow, PyTorch,

• Hands-on experience with GenAI orchestration frameworks such as LangGraph, CrewAI

• Hands-on experience with reinforcement learning libraries such as OpenAI Gym, Ray RLlib, or Stable Baselines.

• Hands-on industrial experience with applied machine learning domains such as deep learning, NLP, GenAI.

Desirable skills/experience:

• Contributions to open-source projects. If you meet these criteria, please highlight merged GitHub PRs in your application.

• Strong publication record in the field of AI.

• Experience designing multi-agent systems in the pharmaceutical sector.

• Experience delivering machine learning projects with applications in pharmaceutical development, chemical engineering or chemistry.

• Experience with one or more of the following applied machine learning domains such as transfer learning, federated learning, few/zero shot learning, meta learning, explainable AI.

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

AstraZeneca is a place where change is embraced, and new solutions are trialed with patients and business in mind. Here, technology is a key lever for delivering medicines quickly, affordably, and sustainably. Our diverse workforce is united by curiosity, sharing learnings to scale fast. Be part of a digitally-enabled environment that impacts all parts of the business,from robotic process automation to machine learning for quality batches,while contributing to society and the planet.

Ready to make a difference? Apply now to join our team!

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We're looking for a Backend Engineer to help bring large-scale GenAI systems to production. In this role, you'll build the core infrastructure that powers AI products for some of the world's largest enterprises,designing scalable APIs, distributed data systems, and robust deployment pipelines that enable production-grade reliability and performance.

This is a rare opportunity to be at the center of the GenAI revolution, solving hard backend and infrastructure challenges that make AI truly work at enterprise scale. If you're excited about shaping how AI systems are deployed and scaled in the real world, we want to hear from you.

At Scale, we don't just follow AI advancements , we lead them. Backed by deep expertise in data, infrastructure, and model deployment, we are uniquely positioned to solve the hardest problems in AI adoption. Join us in shaping the future of enterprise AI, where your work will directly impact how businesses operate, innovate, and grow in the age of GenAI.

Responsibilities

• Design, build, and scale backend systems that power enterprise GenAI products, focusing on reliability, performance, and deployment across both Scale's and customers' infrastructure.
• Develop core services and APIs that integrate AI models and enterprise data sources securely and efficiently, enabling production-scale AI adoption.
• Architect scalable distributed systems for data processing, inference, and orchestration of large-scale GenAI workloads.
• Optimize backend performance for latency, throughput, and cost,ensuring AI applications can operate at enterprise scale across hybrid and multi-cloud environments.
• Manage and evolve cloud infrastructure (AWS, Azure, or GCP), driving automation, observability, and security for large-scale AI deployments.
• Collaborate with ML and product teams to bring cutting-edge GenAI models into production through efficient APIs, model serving systems, and evaluation frameworks.
• Continuously improve reliability and scalability, applying strong engineering practices to make AI systems robust, maintainable, and enterprise-ready.

Ideal Candidate

• 4+ years of experience developing large-scale backend or infrastructure systems, with a strong emphasis on distributed services, reliability, and scalability.
• Proficiency in Python or TypeScript, with experience designing high-performance APIs and backend architectures using frameworks such as FastAPI, Flask, Express, or NestJS.
• Deep familiarity with cloud infrastructure (AWS and Azure preferred), including container orchestration (Kubernetes, Docker) and Infrastructure-as-Code tools like Terraform.
• Experience managing data systems such as relational and NoSQL databases (PostgreSQL, DynamoDB, etc.) and building pipelines for data-intensive applications.
• Hands-on experience with GenAI applications, model integration, or AI agent systems,understanding how to deploy, evaluate, and scale AI workloads in production.
• Strong understanding of observability, CI/CD, and security best practices for running services in enterprise or multi-tenant environments.
• Ability to balance rapid iteration with production-grade quality, shipping reliable backend systems in fast-paced environments.

Collaborative mindset, working closely with ML, infra, and product teams to bring complex GenAI systems into production at enterprise scale.

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Estimated Base Salary $295K – $445K

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

Team Description

OpenAI is looking for exceptional researchers to join the Post-Training Frontiers team, which is responsible for post-training the agentic models we ship across Codex, the API, ChatGPT Thinking, and ChatGPT Pro. The Post-Training Frontiers team sets up the pipeline for deciding which integrations can go into the post-training run, develops its own horizontal improvements to the model, and trains the final model.

Responsibilities

• Own end-to-end research and engineering projects that improve the final post-training of OpenAI’s agentic models.

• Decide, together with partner teams, which integrations are ready for inclusion in major model runs.

• Develop horizontal model improvements across factuality, instruction following, tool/function calling, multi-agent behavior, reasoning-effort calibration, and other broad capabilities.

• Build and improve training, evaluation, grading, and data infrastructure for large-scale RL/post-training runs.

• Create evals and diagnostics that help us understand whether a model is ready to ship.

• Improve the feedback loop from real product usage into post-training, including better ways to learn from implicit user feedback.

• Collaborate closely with Codex, API, ChatGPT, product, training, and other post-training teams to make frontier models more useful, reliable, and agentic.

Nice to have

• Experience with large-scale model training or RL systems.

• Experience building evals, graders, reward models, or data pipelines for LLM training.

• Experience with coding agents, tool-using agents, browser/computer-use agents, function calling, or multi-agent systems.

• Background in quant, systems, infra, or other environments where you built reliable machinery for high-stakes experimentation.

• Evidence of strong product taste, especially around writing, design, code generation, or agent workflows.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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We’re looking for a Data Infrastructure Manager to lead a team of talented engineers building and scaling the data infrastructure that powers Microsoft’s consumer AI. This role sits at the intersection of technical leadership and people management. You’ll set the technical direction for large-scale data and ML pipelines, AI agentic workflows, and intelligent systems while growing a high-performing team of ICs.

If you’ve architected big data platforms from the ground up and are now ready to multiply your impact through others, including on some of the most exciting AI infrastructure challenges in the industry, we want to hear from you.

You’ll bring:

Deep technical expertise in big data and distributed systems A track record of leading and developing engineering talent A passion for automation, observability, and operational excellence The ability to translate complex technical strategy into clear, executable plans Empathy, collaboration, and a growth mindset

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of Respect, Integrity, and Accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Responsibilities:

Team Leadership & People Development Hire, mentor, and develop a team of Data Infrastructure Engineers, fostering a culture of technical excellence, ownership, and continuous growth. Conduct regular 1:1s, set clear goals, and provide actionable feedback to support each engineer’s career development. Build and sustain an inclusive, collaborative team environment aligned with Microsoft’s values of Respect, Integrity, Accountability, and Inclusion.

Technical Strategy & Architecture Define and drive the technical vision for a scalable, reliable, and observable Big Data Infrastructure serving mission-critical AI applications, including agentic and intelligent systems. Lead technical design reviews, establish engineering standards, and ensure a clean, secure, and well-documented codebase. Partner with engineers to architect data solutions across storage, compute, and analytics layers, including the pipelines and orchestration frameworks that underpin AI agent workflows, balancing long-term scalability with near-term delivery.

Platform & Operations Champion DevOps and SRE best practices across the team, including automated deployments, service monitoring, and incident response. Guide the team in building a self-service big data platform that empowers data engineers, researchers, and partner teams. Oversee robust CI/CD pipelines and infrastructure-as-code practices using tools like Bicep, Terraform, and ARM. Lead capacity planning and drive proactive resolution of bottlenecks in data pipelines and infrastructure.

Cross-Functional Collaboration Act as a key technical partner to Data Engineers, Data Scientists, AI Researchers, ML Engineers, and Developers to deliver secure, seamless big data workflows. Collaborate with Security teams to uphold strong infrastructure security practices (IAM, OAuth, Kerberos). Represent the team in planning and prioritization discussions, translating organizational goals into actionable engineering roadmaps.

Qualifications:

Required Qualifications: Bachelor’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 6+ years experience in business analytics, data science, software development, data modeling or data engineering work OR Master’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years experience in business analytics, data science, software development, or data engineering work OR equivalent experience.

Preferred Qualifications: Master’s Degree in Computer Science or related technical field AND 10+ years of technical engineering experience OR Bachelor’s Degree AND 14+ years, OR equivalent experience. 5+ years in Big Data Infrastructure, DevOps, SRE, or Platform Engineering. 5+ years of hands-on experience with distributed systems from bare-metal to cloud-native environments. 5+ years overseeing or contributing to containerized application deployments using Kubernetes and Helm/Kustomize. Solid scripting and automation fluency in Python, Bash, or PowerShell. Proven track record managing CI/CD pipelines, release automation, and production incident response. Hands-on expertise with modern data platforms like Databricks, including deep familiarity with relational and NoSQL databases, key-value stores, Spark compute engines, distributed file systems (e.g., HDFS, ADLS Gen2), and messaging systems (e.g., Event Hub, Kafka, RabbitMQ). Proven experience with cloud-native infrastructure across Azure, AWS, or GCP. Strong collaboration history with Data Engineers, Data Scientists, ML Engineers, Networking, and Security teams. Experience with agentic workflow infrastructure, including orchestration frameworks (e.g., Semantic Kernel, AutoGen), retrieval pipelines, and the data infrastructure patterns that support multi-agent systems at scale. Familiarity with modern web stacks: TypeScript, Node.js, React, and optionally PHP.

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We’re looking for a Data Infrastructure Manager to lead a team of talented engineers building and scaling the data infrastructure that powers Microsoft’s consumer AI. This role sits at the intersection of technical leadership and people management. You’ll set the technical direction for large-scale data and ML pipelines, AI agentic workflows, and intelligent systems while growing a high-performing team of ICs.

If you’ve architected big data platforms from the ground up and are now ready to multiply your impact through others, including on some of the most exciting AI infrastructure challenges in the industry, we want to hear from you.

You’ll bring:

Deep technical expertise in big data and distributed systems A track record of leading and developing engineering talent A passion for automation, observability, and operational excellence The ability to translate complex technical strategy into clear, executable plans Empathy, collaboration, and a growth mindset

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of Respect, Integrity, and Accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50-mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

Responsibilities:

Team Leadership & People Development Hire, mentor, and develop a team of Data Infrastructure Engineers, fostering a culture of technical excellence, ownership, and continuous growth. Conduct regular 1:1s, set clear goals, and provide actionable feedback to support each engineer’s career development. Build and sustain an inclusive, collaborative team environment aligned with Microsoft’s values of Respect, Integrity, Accountability, and Inclusion.

Technical Strategy & Architecture Define and drive the technical vision for a scalable, reliable, and observable Big Data Infrastructure serving mission-critical AI applications, including agentic and intelligent systems. Lead technical design reviews, establish engineering standards, and ensure a clean, secure, and well-documented codebase. Partner with engineers to architect data solutions across storage, compute, and analytics layers, including the pipelines and orchestration frameworks that underpin AI agent workflows, balancing long-term scalability with near-term delivery.

Platform & Operations Champion DevOps and SRE best practices across the team, including automated deployments, service monitoring, and incident response. Guide the team in building a self-service big data platform that empowers data engineers, researchers, and partner teams. Oversee robust CI/CD pipelines and infrastructure-as-code practices using tools like Bicep, Terraform, and ARM. Lead capacity planning and drive proactive resolution of bottlenecks in data pipelines and infrastructure.

Cross-Functional Collaboration Act as a key technical partner to Data Engineers, Data Scientists, AI Researchers, ML Engineers, and Developers to deliver secure, seamless big data workflows. Collaborate with Security teams to uphold strong infrastructure security practices (IAM, OAuth, Kerberos). Represent the team in planning and prioritization discussions, translating organizational goals into actionable engineering roadmaps.

Qualifications:

Required Qualifications: Bachelor’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 6+ years experience in business analytics, data science, software development, data modeling or data engineering work OR Master’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years experience in business analytics, data science, software development, or data engineering work OR equivalent experience.

Preferred Qualifications: Master’s Degree in Computer Science or related technical field AND 10+ years of technical engineering experience OR Bachelor’s Degree AND 14+ years, OR equivalent experience. 5+ years in Big Data Infrastructure, DevOps, SRE, or Platform Engineering. 5+ years of hands-on experience with distributed systems from bare-metal to cloud-native environments. 5+ years overseeing or contributing to containerized application deployments using Kubernetes and Helm/Kustomize. Solid scripting and automation fluency in Python, Bash, or PowerShell. Proven track record managing CI/CD pipelines, release automation, and production incident response. Hands-on expertise with modern data platforms like Databricks, including deep familiarity with relational and NoSQL databases, key-value stores, Spark compute engines, distributed file systems (e.g., HDFS, ADLS Gen2), and messaging systems (e.g., Event Hub, Kafka, RabbitMQ). Proven experience with cloud-native infrastructure across Azure, AWS, or GCP. Strong collaboration history with Data Engineers, Data Scientists, ML Engineers, Networking, and Security teams. Experience with agentic workflow infrastructure, including orchestration frameworks (e.g., Semantic Kernel, AutoGen), retrieval pipelines, and the data infrastructure patterns that support multi-agent systems at scale. Familiarity with modern web stacks: TypeScript, Node.js, React, and optionally PHP.

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We're seeking a hands-on Principal Software Engineer to lead the development of security features and innovative solutions that harness agentic AI to both protect our customers and enable new agentic capabilities in Copilot. You'll design, build, and ship AI-powered defenses, secure orchestration frameworks, and enabling technologies that empower Copilot to act safely and responsibly at scale.

This role demands deep engineering expertise, creativity in applying agentic AI to security challenges, and a passion for building systems that balance innovation with trust. Your work will directly shape how hundreds of millions of users experience safe, trustworthy, and innovative AI. You'll be at the forefront of defining how agentic AI can proactively defend users, mitigate emerging threats, and unlock new secure scenarios,making a global impact on Microsoft's most transformative products.

As a Principal Software Engineer, you will:

• Develop and ship agentic AI-powered security features that proactively protect users from threats such as prompt injection, adversarial manipulation, and abuse of agentic workflows.
• Design and implement secure orchestration frameworks that enable Copilot to safely delegate, coordinate, and execute actions across devices, services, and platforms.
• Invent and apply new intelligent agents that leverage information flow analysis and apply common sense and judgement guardrails for security and privacy.
• Collaborate with product, engineering, security, privacy, and AI teams to drive adoption of agentic security patterns and best practices across Copilot and MAI.
• Establish and monitor key metrics for agentic AI security and innovation, using data-driven insights to continuously improve defenses and enablement.
• Align with central Microsoft security and AI roadmaps, influencing platform capabilities and landing them in Copilot and MAI consumer scenarios.
• Document and evangelize secure agentic AI patterns, ensuring they address novel risks, support safe delegation, and enable responsible orchestration of actions.
• Mentor engineers and foster a culture of secure innovation, balancing rapid development with rigorous protection for customers.

Qualifications:

• Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
• 8+ years in technical engineering roles building large-scale services.
• 6+ years hands-on experience designing and operating security-critical or AI-powered systems at scale, including agentic AI, secure orchestration, or advanced threat defenses.
• Proven ability to design, build, and ship agentic AI features or frameworks.
• Ability to clearly explain complex systems and security concepts to technical and non-technical stakeholders and influence cross-org roadmaps.
• Experience building production agent systems using frameworks such as LangGraph, Amazon Strands SDK, or similar platforms; familiarity with agentic design patterns including tool calling, multi-agent coordination, and secure delegation patterns.
• Hands-on experience with distributed training frameworks (Ray, Slurm, HPC), containerization and orchestration technologies (Docker, Kubernetes) for ML model deployment, and ML lifecycle management in production environments.
• Experience designing evaluation frameworks for LLM-based applications and implementing observability for agent systems using tools such as Phoenix, MLFlow, LangFuse, or custom eval harnesses; understanding of AI safety evaluation methodologies including adversarial testing and red-teaming.
• Experience integrating with Azure AI services, Azure OpenAI Service, or Microsoft security platforms (Azure AD, Defender, Purview).
• Track record of mentoring experienced engineers, driving adoption of secure agentic AI standards across product teams, and influencing technical roadmaps while balancing innovation velocity with fundamentals.

#MicrosoftAI Software Engineering IC5 – The typical base pay range for this role across the U.S. is USD $139,900 – $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 – $304,200 per year.

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We’re looking for a Data Infrastructure Manager to lead a team of talented engineers building and scaling the data infrastructure that powers Microsoft’s consumer AI. This role sits at the intersection of technical leadership and people management. You’ll set the technical direction for large-scale data and ML pipelines, AI agentic workflows, and intelligent systems while growing a high-performing team of ICs.

If you’ve architected big data platforms from the ground up and are now ready to multiply your impact through others, including on some of the most exciting AI infrastructure challenges in the industry, we want to hear from you.

Deep technical expertise in big data and distributed systems A track record of leading and developing engineering talent A passion for automation, observability, and operational excellence The ability to translate complex technical strategy into clear, executable plans Empathy, collaboration, and a growth mindset

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of Respect, Integrity, and Accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50-mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

Team Leadership & People Development Hire, mentor, and develop a team of Data Infrastructure Engineers, fostering a culture of technical excellence, ownership, and continuous growth. Conduct regular 1:1s, set clear goals, and provide actionable feedback to support each engineer’s career development. Build and sustain an inclusive, collaborative team environment aligned with Microsoft’s values of Respect, Integrity, Accountability, and Inclusion.

Technical Strategy & Architecture Define and drive the technical vision for a scalable, reliable, and observable Big Data Infrastructure serving mission-critical AI applications, including agentic and intelligent systems. Lead technical design reviews, establish engineering standards, and ensure a clean, secure, and well-documented codebase. Partner with engineers to architect data solutions across storage, compute, and analytics layers, including the pipelines and orchestration frameworks that underpin AI agent workflows, balancing long-term scalability with near-term delivery.

Platform & Operations Champion DevOps and SRE best practices across the team, including automated deployments, service monitoring, and incident response. Guide the team in building a self-service big data platform that empowers data engineers, researchers, and partner teams. Oversee robust CI/CD pipelines and infrastructure-as-code practices using tools like Bicep, Terraform, and ARM. Lead capacity planning and drive proactive resolution of bottlenecks in data pipelines and infrastructure.

Cross-Functional Collaboration Act as a key technical partner to Data Engineers, Data Scientists, AI Researchers, ML Engineers, and Developers to deliver secure, seamless big data workflows. Collaborate with Security teams to uphold strong infrastructure security practices (IAM, OAuth, Kerberos). Represent the team in planning and prioritization discussions, translating organizational goals into actionable engineering roadmaps.

Qualifications Bachelor’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 6+ years experience in business analytics, data science, software development, data modeling or data engineering work OR Master’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years experience in business analytics, data science, software development, or data engineering work OR equivalent experience.

Preferred Qualifications Master’s Degree in Computer Science or related technical field AND 10+ years of technical engineering experience OR Bachelor’s Degree AND 14+ years, OR equivalent experience. 5+ years in Big Data Infrastructure, DevOps, SRE, or Platform Engineering. 5+ years of hands-on experience with distributed systems from bare-metal to cloud-native environments. 5+ years overseeing or contributing to containerized application deployments using Kubernetes and Helm/Kustomize. Solid scripting and automation fluency in Python, Bash, or PowerShell. Proven track record managing CI/CD pipelines, release automation, and production incident response. Hands-on expertise with modern data platforms like Databricks, including deep familiarity with relational and NoSQL databases, key-value stores, Spark compute engines, distributed file systems (e.g., HDFS, ADLS Gen2), and messaging systems (e.g., Event Hub, Kafka, RabbitMQ). Proven experience with cloud-native infrastructure across Azure, AWS, or GCP. Strong collaboration history with Data Engineers, Data Scientists, ML Engineers, Networking, and Security teams. Experience with agentic workflow infrastructure, including orchestration frameworks (e.g., Semantic Kernel, AutoGen), retrieval pipelines, and the data infrastructure patterns that support multi-agent systems at scale. Familiarity with modern web stacks: TypeScript, Node.js, React, and optionally PHP.

#MicrosoftAI #MAIDPS #mai-datainsights #mai-datainsights

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We’re seeking a hands-on Principal Software Engineer to lead the development of security features and innovative solutions that harness agentic AI to both protect our customers and enable new agentic capabilities in Copilot. You’ll design, build, and ship AI-powered defenses, secure orchestration frameworks, and enabling technologies that empower Copilot to act safely and responsibly at scale.

This role demands deep engineering expertise, creativity in applying agentic AI to security challenges, and a passion for building systems that balance innovation with trust. Your work will directly shape how hundreds of millions of users experience safe, trustworthy, and innovative AI. You’ll be at the forefront of defining how agentic AI can proactively defend users, mitigate emerging threats, and unlock new secure scenarios,making a global impact on Microsoft’s most transformative products.

As employees, we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. This expectation is subject to local law and may vary by jurisdiction.

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About the Role Copilot for consumers is entering a new era of agentic AI, where intelligent agents act on behalf of users across Windows, Edge, web, mobile, and third-party products. We’re seeking a Senior Software Engineer to help develop security features and solutions that harness agentic AI to protect customers and enable new capabilities in Copilot.

Responsibilities Develop and ship agentic AI-powered security features that protect users from threats such as prompt injection, adversarial manipulation, and abuse of agentic workflows. Implement secure orchestration frameworks that enable Copilot to safely delegate, coordinate, and execute actions across devices, services, and platforms. Invent and apply new intelligent agents that leverage information flow analysis and apply common sense and judgement guardrails for security and privacy. Collaborate with product, engineering, security, privacy, and AI teams to adopt agentic security patterns and best practices across Copilot and MAI. Monitor key metrics for agentic AI security and innovation, using data-driven insights to improve defenses and enablement. Document secure agentic AI patterns, ensuring they address novel risks, support safe delegation, and enable responsible orchestration of actions.

Qualifications Required Qualifications: Bachelor’s Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Preferred Qualifications: 3+ years in technical engineering roles building large-scale services. Hands-on experience designing and operating security-critical or AI-powered systems at scale, including agentic AI, secure orchestration, or advanced threat defenses. Proven ability to design, build, and ship agentic AI features or frameworks. Agentic AI Development & Orchestration: Experience building production agent systems using frameworks such as LangGraph, Amazon Strands SDK, or similar platforms; familiarity with agentic design patterns including tool calling, multi-agent coordination, and secure delegation patterns. Hands-on experience with distributed training frameworks (Ray, Slurm, HPC), containerization and orchestration technologies (Docker, Kubernetes) for ML model deployment, and ML lifecycle management in production environments. Experience designing evaluation frameworks for LLM-based applications and implementing observability for agent systems using tools such as Phoenix, MLFlow, LangFuse, or custom eval harnesses; understanding of AI safety evaluation methodologies including adversarial testing and red-teaming. Experience integrating with Azure AI services, Azure OpenAI Service, or Microsoft security platforms (Azure AD, Defender, Purview). Track record of mentoring less experienced engineers, driving adoption of standards and best practices across teams, and influencing technical roadmaps while balancing innovation velocity with fundamentals.

#MicrosoftAI Software Engineering IC4 The typical base pay range for this role across the U.S. is USD $119,800 – $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 – $258,000 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

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We're looking for a Backend Engineer to help bring large-scale GenAI systems to production. In this role, you'll build the core infrastructure that powers AI products for some of the world's largest enterprises,designing scalable APIs, distributed data systems, and robust deployment pipelines that enable production-grade reliability and performance.

This is a rare opportunity to be at the center of the GenAI revolution, solving hard backend and infrastructure challenges that make AI truly work at enterprise scale. If you're excited about shaping how AI systems are deployed and scaled in the real world, we want to hear from you.

At Scale, we don't just follow AI advancements , we lead them. Backed by deep expertise in data, infrastructure, and model deployment, we are uniquely positioned to solve the hardest problems in AI adoption. Join us in shaping the future of enterprise AI, where your work will directly impact how businesses operate, innovate, and grow in the age of GenAI.

Responsibilities

• Design, build, and scale backend systems that power enterprise GenAI products, focusing on reliability, performance, and deployment across both Scale's and customers' infrastructure.

• Develop core services and APIs that integrate AI models and enterprise data sources securely and efficiently, enabling production-scale AI adoption.

• Architect scalable distributed systems for data processing, inference, and orchestration of large-scale GenAI workloads.

• Optimize backend performance for latency, throughput, and cost,ensuring AI applications can operate at enterprise scale across hybrid and multi-cloud environments.

• Manage and evolve cloud infrastructure (AWS, Azure, or GCP), driving automation, observability, and security for large-scale AI deployments.

• Collaborate with ML and product teams to bring cutting-edge GenAI models into production through efficient APIs, model serving systems, and evaluation frameworks.

• Continuously improve reliability and scalability, applying strong engineering practices to make AI systems robust, maintainable, and enterprise-ready.

Ideal Candidate

• 4+ years of experience developing large-scale backend or infrastructure systems, with a strong emphasis on distributed services, reliability, and scalability.

• Proficiency in Python or TypeScript, with experience designing high-performance APIs and backend architectures using frameworks such as FastAPI, Flask, Express, or NestJS.

• Deep familiarity with cloud infrastructure (AWS and Azure preferred), including container orchestration (Kubernetes, Docker) and Infrastructure-as-Code tools like Terraform.

• Experience managing data systems such as relational and NoSQL databases (PostgreSQL, DynamoDB, etc.) and building pipelines for data-intensive applications.

• Hands-on experience with GenAI applications, model integration, or AI agent systems,understanding how to deploy, evaluate, and scale AI workloads in production.

• Strong understanding of observability, CI/CD, and security best practices for running services in enterprise or multi-tenant environments.

• Ability to balance rapid iteration with production-grade quality, shipping reliable backend systems in fast-paced environments.

Collaborative mindset, working closely with ML, infra, and product teams to bring complex GenAI systems into production at enterprise scale.

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Lead applied ML engineering on Scale's Applied ML team, powering data infrastructure for leading agentic LLMs (ChatGPT, Gemini, Llama). You will build scalable multi-agent systems to validate agentic reasoning and behaviours, scale human expertise, and drive research into real-world agent reliability failures despite strong benchmarks, shipping production fixes.

Responsibilities

• Build and deploy multi-agent systems for agentic reasoning validation
• Develop pipelines to detect errors and scale human judgment
• Combine classical ML, LLMs, and multi-agent techniques for reliability
• Lead research into agent failure modes and ship fixes
• Use AI tools to speed prototyping and iteration
• Build data-driven evaluations and deploy rapid improvements
• Integrate systems into Scale's platform

Ideal Candidate

• PhD or MSc in Computer Science, Mathematics, Statistics, or related field
• 3+ years shipping scaled production ML systems
• Demonstrated real-world impact
• Mastery of PyTorch, TensorFlow, JAX, or scikit-learn
• Deep expertise in agentic LLMs and multi-agent systems
• Strong software engineering and microservices (AWS/GCP)
• Rapid, data-driven iteration
• Proficiency using AI tools to accelerate work
• Strong research depth with practical bias
• Excellent cross-functional communication

Nice to Have

• Experience prototyping agent evaluation/reliability systems
• Human-in-the-loop or annotation pipeline work
• Open-source contributions in agents, evaluation, or alignment
• Publications on agent reliability (NeurIPS, ICML, ICLR)

Compensation

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity-based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

About Us

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

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Responsibilities:

• Design, develop, and deploy Cresta's AI Agent solutions and proprietary models.
• Focus on practical AI challenges such as improving reasoning, planning capabilities, and evaluation in real-world scenarios.
• Collaborate with cross-functional teams including front-end and back-end software engineers to integrate AI Agents into Cresta's customer solutions.
• Lead initiatives to scale AI systems for production environments, ensuring performance and reliability across use cases.
• Contribute to solving cutting-edge problems in AI and help define the future roadmap for Cresta's AI Agents.
• Innovate and research ways to improve security, cost-efficiency, and reliability of AI systems.

Qualifications:

• Bachelor's or Master's Degree in Computer Science, Mathematics, or a related field.
• 2+ years of hands-on industry experience with AI and machine learning, preferably with experience working with LLMs in large-scale production environments.
• Solid knowledge of machine learning concepts and methods, especially those related to NLP, Generative AI, and working with LLMs.
• Practical knowledge of modern machine learning frameworks and technologies (e.g., PyTorch, Tensorflow, Hugging Face, NumPy), as well as experience with distributed systems and cloud-based AI infrastructure.
• Strong problem-solving and strategic thinking abilities, with a proven ability to lead cross-functional teams and work collaboratively to deliver innovative AI solutions in production.
• A passion for driving AI adoption and pushing the boundaries of AI technology into real-world applications, with an ability to mentor junior engineers and influence strategic decisions across the organization.

Perks & Benefits:

• We offer Cresta employees a variety of medical, dental, and vision plans, designed to fit you and your family's needs.
• Paid parental leave to support you and your family.
• Monthly Health & Wellness allowance.
• Work from home office stipend to help you succeed in a remote environment.
• Lunch reimbursement for in-office employees.
• PTO: 3 weeks in Canada.

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Senior Software Engineer, AI Products (India)

Company Overview

Airbnb is a global online marketplace for booking accommodations, with over 5 million hosts and 2 billion guest arrivals.

The Community You Will Join

The Airfam Products team exists to make every Airbnb employee more productive through a unified digital headquarters experience. As part of a 13-person cross-functional team of engineers, designers, researchers, and product managers, you'll work on platforms that serve Airbnb's entire global workforce. Our portfolio includes One Airbnb (the company's internal cultural hub with enterprise search, people profiles, and AI-powered chat), OneChat (Airbnb's enterprise AI assistant enabling secure LLM interactions), and a suite of tools that power how employees discover information, connect with colleagues, and get work done. You'll be joining the AI for Non-Developers workstream, focused on expanding AI productivity tools to all Airbnb employees,building OneChat Agents, deep research capabilities, artifact creation tools, and task automation that make AI accessible to everyone, regardless of technical background.

The Difference You Will Make

As a Senior Software Engineer on the Airfam Products team, you'll be instrumental in building Airbnb's next generation of AI-powered employee experience platforms. Your work will be a force multiplier for the entire company,every AI feature you ship, every system you architect, and every engineer you mentor will amplify productivity across Airbnb's global workforce. You will:

• Democratize AI by building tools that empower non-technical employees to leverage the power of LLMs
• Drive innovation by taking AI prototypes from concept to production at scale
• Shape the future of how Airbnb employees work, collaborate, and discover information

A Typical Day

• Lead the technical design and implementation of LLM-powered features for OneChat and enterprise AI tools, including RAG pipelines, AI agents, and prompt optimization
• Partner with product managers, designers, and cross-functional teams to translate user problems into AI-powered solutions that serve Airbnb's global workforce
• Develop and iterate on agentic AI capabilities, including multi-step reasoning, tool use, and context-aware decision-making
• Implement evaluation pipelines and quality systems to measure model performance, detect hallucinations, and ensure responsible AI practices
• Own production AI systems end-to-end, including deployment strategies, monitoring, alerting, and incident response
• Collaborate with the DevAI team on AirChat SDK integrations, MCP (Model Context Protocol) implementations, and Glean Action Packs
• Mentor engineers (L6-L8) through design reviews, architecture discussions, and pair programming sessions
• Stay current with the rapidly evolving GenAI landscape, evaluating new models and techniques for potential application
• Balance hands-on technical contributions with technical leadership activities

Your Expertise

• 8+ years of software engineering experience, with significant focus on building production AI/ML systems
• 2+ years of hands-on experience with Large Language Models (LLMs), including fine-tuning, prompt engineering, embeddings, and retrieval-augmented generation (RAG)
• Strong proficiency in backend technologies (TypeScript, Go, or Java)
• Strong backend and distributed systems expertise, including API design (REST, GraphQL) and cloud infrastructure (AWS, GCP, or Azure)
• Track record of shipping AI-powered products from prototype to production
• Proven ability to collaborate cross-functionally and influence without authority
• Excellent communication skills with ability to distill complex technical concepts for diverse audiences
• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience

Preferred

• Master's or PhD in Computer Science, Machine Learning, or related field
• Experience building AI agents and multi-agent systems, preferably using Claude
• Experience building integrations using MCP
• Experience with containerization and orchestration (Docker, Kubernetes)
• Background in building enterprise-grade internal tools and developer productivity platforms
• Experience with frontend technologies (React, Next.js) for full-stack AI product development
• Contributions to open-source Gen AI/ML projects or publications at top venues

Your Location

This position is based in Bangalore, India with a hybrid work arrangement. You'll collaborate with teammates across global time zones, with primary alignment to Pacific Time for key meetings.

Our Commitment to Inclusion & Belonging

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

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As a Staff Engineer, AI Security on the AppSec team, you'll lead autonomous defense for the AI lifecycle. Build multi-agent frameworks and secure gateways while integrating real-time security gates and identity standards. By mentoring Security and R&D to define the MLSecOps roadmap, you'll ensure a 'secure-by-default' future for agentic workflows and resilient AI innovation.

Responsibilities:

Serve as the primary subject matter expert for all AI and machine learning security initiatives across security and R&D.

Design and manage AI gateways to provide a centralized control plane for authentication and authorization and rate limiting across all model and tool interactions.

Build and maintain an autonomous security agentic framework that utilizes multi agent orchestration for end to end investigation and alert triage and remediation.

Develop agentic identity models using OAuth 2.1 to propagate identity across trust boundaries and prevent the confused deputy problem.

Help govern the AI augmented software development lifecycle by integrating real time security gates into the developer environment and CI/CD pipeline.

Manage Agentic Security Solutions that secure AI lifecycle and manage AI workloads at runtime.

Author company wide AI security standards and implement these security checks across Twilio's stack.

Implement human in the loop checkpoints and transactional safety protocols for high impact or destructive agentic actions.

Partner with engineering leadership to set the long term roadmap for identity centric security and automated posture management.

Act as a knowledge multiplier by mentoring security engineers and developing secure by default paved road templates for R&D teams

Qualifications:

8+ years of experience in security engineering with at least 3 years focused on AI or machine learning security operations (MLSecOps).

Expertise in orchestrating multi-agent systems with AWS Strands, LangGraph, and CrewAI, specializing in runtime isolation, PII redaction, and defending against indirect prompt injection in agentic environments.

Hands-on experience with AI-specific frameworks (e.g., MITRE ATLAS, MAESTRO, OWASP Top 10 for LLMs/Agents/MCP) to threat model and defend against a wide spectrum of risks, including direct/indirect prompt injection, training data poisoning, tool poisoning, and data exfiltration within agentic workflows.

Proficiency in securing end-to-end AI pipelines, from data ingestion and training to model deployment and monitoring.

Strong communication skills to translate complex AI risks into actionable business logic for stakeholders.

Desired:

Hands-on experience in modern application security tooling including SAST and SCA and DAST with experience adapting these tools to catch AI specific vulnerabilities like indirect prompt injection.

Expertise in identity standards including OAuth 2.1 and PKCE.

Experience with AI Red Teaming and conducting adversarial simulations against Large Language Models (LLMs) and agentic systems.

Proficiency in at least one general programming language (Python, Go, etc) with experience in container security and workload isolation.

Proven ability to operate with autonomy and drive high impact outcomes in ambiguous environments by identifying and executing on critical projects without predefined roadmaps or direct supervision.

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This role goes beyond building models; it's about designing agentic systems, AI-assisted workflows, and data-driven decision engines that help the company scale faster than headcount.

You will be at the forefront of developing the next generation of autonomous systems that power both customer-facing products and internal operations, from optimizing payment experiences to accelerating development, testing, troubleshooting, and product creation.

Responsibilities:

• Architect, build, and deploy LLM-powered applications that augment and automate key workflows across Yuno, from customer service and new product development to internal agentic workflows that optimize critical company processes.

• Design autonomous AI systems that can execute technical analysis, testing, troubleshooting, and decision-making at scale.

• Develop AI-driven tools that create measurable business impact, improving efficiency, accelerating innovation, and driving revenue growth.

Operational Intelligence & Scalability:

• Identify areas across Yuno where AI can generate efficiency gains, reducing manual work, optimizing processes, and enabling smarter operations.

• Build AI systems that enable Yuno to scale without exponential growth in headcount, thereby creating sustainable productivity and organizational intelligence.

Data & Model Optimization:

• Lead fine-tuning and contextual optimization of AI models using Yuno's proprietary data.

• Continuously refine performance through structured feedback loops, observability metrics, and user interaction data.

• Ensure adherence to privacy, compliance, and ethical AI principles in all model development.

Cross-Functional Collaboration & Innovation:

• Work closely with data, product, and infrastructure teams to define the long-term AI roadmap for Yuno.

• Experiment with emerging AI technologies to identify new capabilities that can drive differentiation and strategic advantage.

• Contribute to a culture of experimentation, rapid iteration, and continuous learning across the AI function.

The skills you need:

• 5+ years of professional experience in AI/ML development, with at least 2 years focused on LLMs, RAG, or agentic systems.

• Strong engineering and product mindset, capable of balancing technical depth with strategic impact.

• Exceptional communication and collaboration skills to work across product, engineering, and data functions.

• Passion for pushing the boundaries of applied AI and creating systems that drive real business transformation.

• Willing to work from the Hyderabad office.

Minimum Qualifications:

• LLMs & RAG: Proven experience designing and deploying systems using models like GPT, Claude, Gemini, or similar, including Retrieval-Augmented Generation (RAG) pipelines and contextual retrieval systems.

• AI Agents & Multi-Agent Systems: Hands-on experience with Crew.ai, LangChain, LangGraph, or similar frameworks to build orchestrated agentic workflows.

• Fine-Tuning & Context Engineering: Expertise in supervised fine-tuning (SFT), LoRA, or custom dataset adaptation for domain-specific tasks.

• Programming & Frameworks: Proficiency in Python, GO, and AI/ML libraries such as PyTorch, TensorFlow, or JAX.

• AI Infrastructure: Experience designing scalable, production-ready AI systems in AWS, GCP, or Azure, with a deep understanding of vector databases, model serving, and inference optimization.

• Observability & Monitoring: Familiarity with LangSmith, LangFuse, or equivalent tools for tracking, debugging, and evaluating LLM performance.

• API Integration: Expertise in integrating AI systems with RESTful APIs and internal platforms to create seamless, usable products.

Preferred Qualifications:

• Experience using LlamaIndex, Hugging Face, or similar open-source frameworks.

• Strong understanding of context optimization, embedding strategies, and knowledge retrieval.

• Familiarity with MLOps, CI/CD pipelines, and production deployment best practices.

• Prior experience in fintech, payments, or other data-intensive and regulated industries.

• Analytical rigor and ability to translate business objectives into measurable AI outcomes.

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About the role: As a Forward Deployed Engineering Intern on the AI Agent team, you’ll support real-world AI deployments and gain hands-on experience with AI systems in customer environments.

Responsibilities:

• Assist in developing and configuring AI agents using Cresta’s platform tools.
• Help build and test integrations between AI agents and external systems (like APIs or data sources).
• Support performance tuning and troubleshooting of AI agent prototypes.
• Work with customers and internal engineering teams to understand requirements and iterate on solutions.
• Participate in team demos, feedback sessions, and learning opportunities.

Nice-to-Haves:

• Experience with APIs, web development, or cloud platforms.
• Prior coursework or projects involving AI/ML concepts or LLMs.
• Exposure to prompt engineering or similar experimentation.

Compensation for this position includes a base salary, equity, and a variety of benefits. Actual base salaries will be based on candidate-specific factors, including experience, skillset, and location, and local minimum pay requirements as applicable. We are actively hiring for this role in the US and Canada. Your recruiter can provide further details.

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As a Senior Software Engineer, your goal will be to ensure that our AI Agents are backed by the most reliable and scalable server solutions. This includes designing and maintaining the server architecture that handles real-world, high-volume interactions and ensures high availability and performance.

This is a unique opportunity to shape the future of AI at Cresta by solving complex problems and bringing breakthrough AI advancements into production environments.

Responsibilities:

• Design, develop, and maintain scalable and robust backend architectures for Cresta's AI Agent solutions and proprietary models.
• Collaborate with cross-functional teams including frontend engineers, machine learning engineers to ensure seamless integration of AI Agents into Cresta's customer solutions.
• Lead initiatives to enhance system scalability and reliability in production environments, focusing on backend services that support AI functionalities.
• Drive efforts to optimize server response times, process large volumes of data efficiently, and maintain high system availability.
• Innovate and implement security measures, cost-reduction strategies, and performance improvements in backend systems supporting AI Agents.

Qualifications We Value:

• Bachelor's degree in Computer Science or a related field.
• 5+ years of experience in backend system architecture, cloud services, or related technology fields.
• Proficient in designing and maintaining clear and robust APIs with a strong understanding of protocols including gRPC, REST.
• Previous experience working with Virtual Agent or AI Agent systems.
• Experience in high-performance database schema design and query optimization, including knowledge of SQL and NoSQL databases.
• Experience in containerized application deployment using Kubernetes and Docker in microservices architectures.
• Experience with cloud environments such as AWS, Azure, or Google Cloud, with a strong understanding of cloud security and compliance standards.

Perks & Benefits:

• Comprehensive medical, dental, and vision coverage with plans to fit you and your family.
• Flexible PTO to take the time you need, when you need it.
• Paid parental leave for all new parents welcoming a new child.
• Retirement savings plan to help you plan for the future.
• Remote work setup budget to help you create a productive home office.
• Monthly wellness and communication stipend to keep you connected and balanced.
• In-office meal program and commuter benefits provided for onsite employees.

Compensation at Cresta:

• Cresta's approach to compensation is simple: recognize impact, reward excellence, and invest in our people. We offer competitive, location-based pay that reflects the market and what each individual brings to the table.
• The posted base salary range represents what we expect to pay for this role in a given location. Final offers are shaped by factors like experience, skills, education, and geography. In addition to base pay, total compensation includes equity and a comprehensive benefits package for you and your family.

Salary Range: $205,000–$270,000 + Offers Equity

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At Cresta, the AI Agent team is on a mission to create state-of-the-art AI Agents that solve practical problems for our customers. We are focused on leveraging the latest technologies in Large Language Models (LLMs) and AI Agent systems, while ensuring that the solutions we develop are cost-effective, secure, and reliable.

As a Senior Software Engineer, your goal will be to ensure that our AI Agents are backed by the most reliable and scalable server solutions. This includes designing and maintaining the server architecture that handles real-world, high-volume interactions and ensures high availability and performance.

Responsibilities:

• Design, develop, and maintain scalable and robust backend architectures for Cresta’s AI Agent solutions and proprietary models.
• Collaborate with cross-functional teams including frontend engineers, machine learning engineers to ensure seamless integration of AI Agents into Cresta’s customer solutions.
• Lead initiatives to enhance system scalability and reliability in production environments, focusing on backend services that support AI functionalities.
• Drive efforts to optimize server response times, process large volumes of data efficiently, and maintain high system availability.
• Innovate and implement security measures, cost-reduction strategies, and performance improvements in backend systems supporting AI Agents.

Qualifications We Value:

• Bachelor’s degree in Computer Science or a related field.
• 5+ years of experience in backend system architecture, cloud services, or related technology fields.
• Proficient in designing and maintaining clear and robust APIs with a strong understanding of protocols including gRPC, REST.
• Previous experience working with Virtual Agent or AI Agent systems.
• Experience in high-performance database schema design and query optimization, including knowledge of SQL and NoSQL databases.
• Experience in containerized application deployment using Kubernetes and Docker in microservices architectures.
• Experience with cloud environments such as AWS, Azure, or Google Cloud, with a strong understanding of cloud security and compliance standards.

Perks & Benefits:

• We offer Cresta employees a variety of medical, dental, and vision plans, designed to fit you and your family’s needs.
• Paid parental leave to support you and your family.
• Monthly Health & Wellness allowance.
• Work from home office stipend to help you succeed in a remote environment.
• Lunch reimbursement for in-office employees.
• PTO: 3 weeks in Canada.

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At Cresta, the AI Agent team is on a mission to create state-of-the-art AI Agents that solve practical problems for our customers. We are focused on leveraging the latest technologies in Large Language Models (LLMs) and AI Agent systems, while ensuring that the solutions we develop are cost-effective, secure, and reliable.

As an AI Agent Engineer, you'll be at the forefront of deploying AI agents that address real-world challenges. In this role, you will work closely with customers as well as our software and machine learning engineers, ensuring high-impact AI Agent deployments and contributing to the continuous improvement of our core AI platform. You’ll develop intelligent AI agents, integrate them seamlessly with external systems and offer hands-on technical expertise to ensure successful deployments.

Responsibilities:

• Develop, configure, deploy, and optimise AI agents using Cresta’s AI platform and tools.
• Build AI agent integrations with external systems (APIs, databases, CRMs, etc.) to ensure seamless workflow integration.
• Optimise AI agent performance (e.g. fine-tune prompts and configurations) and troubleshoot issues in complex enterprise environments.
• Collaborate with customers and internal stakeholders to gather technical requirements and translate business needs into AI Agent solutions.
• Conduct interactive demos and present compelling proof-of-concepts to prospective customers, proactively gather feedback, and iteratively refine solutions to meet objectives.
• Define project milestones, create implementation plans, and coordinate execution with internal teams to ensure on-time delivery. Provide a tight feedback loop to our product and engineering teams , identifying gaps, building custom tooling, and influencing the roadmap through real-world deployment learnings.
• Collaborate with PMs to define agent goals, iterate rapidly based on customer feedback, and shape product capabilities that maximise customer ROI.
• Serve as a trusted technical advisor for the customer, guiding best practices for AI agent adoption and usage. Provide technical guidance on AI agent best practices, including architecture design, security considerations, and scalability planning.

What We're Looking For:

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Experience: 3+ years of full-time working experience in software development/Consulting, AI/ML engineering, or Forward Deployed Engineering.
• Programming Skills: Proficiency in Python and Golang, with the ability to write clean, efficient code.
• AI/ML Knowledge: Familiarity with AI/ML concepts. Hands-on experience with large language models (LLMs), and prompt engineering techniques are strongly preferred.
• AI Agent Frameworks: Strong understanding of general AI agent frameworks, function calling, and retrieval-augmented generation (RAG). Hands-on experience of building such a system is strongly preferred.
• Cloud & DevOps: Experience with cloud platforms (AWS, GCP, or Azure) and DevOps practices (CI/CD, containerisation, monitoring).
• Integration Expertise: Hands-on experience with integrating systems via APIs, webhooks, and data pipelines.
• Communication: Excellent communication and project management skills.
• Analytical Approach: Ability to use data-driven decision-making, including A/B testing and performance monitoring, to refine solutions.
• Collaborative Builder: You thrive in cross-functional environments, working hand-in-hand with PMs and engineers to turn real customer problems into scalable AI solutions.

Perks & Benefits:

• We offer Cresta employees a variety of medical, dental, and vision plans, designed to fit you and your family’s needs.
• Paid parental leave to support you and your family.
• Monthly Health & Wellness allowance.
• Work from home office stipend to help you succeed in a remote environment.
• Lunch reimbursement for in-office employees.
• PTO: 3 weeks in Canada.

XML job scraping automation by YubHub

At Cresta, the AI Agent team is on a mission to create state-of-the-art AI Agents that solve practical problems for our customers. We are focused on leveraging the latest technologies in Large Language Models (LLMs) and AI Agent systems, while ensuring that the solutions we develop are cost-effective, secure, and reliable.

As an AI Agent Engineer, you'll be at the forefront of deploying AI agents that address real-world challenges. In this role, you will work closely with customers as well as our software and machine learning engineers, ensuring high-impact AI Agent deployments and contributing to the continuous improvement of our core AI platform. You’ll develop intelligent AI agents, integrate them seamlessly with external systems and offer hands-on technical expertise to ensure successful deployments.

This position requires strong engineering skills, adaptability, and customer engagement. If you are self-driven, analytical, and eager to leverage AI in practical applications, this role is for you.

Our team is looking for someone with a strong background in software development, AI/ML engineering, or forward deployed engineering. You should have experience with cloud platforms (AWS, GCP, or Azure) and DevOps practices (CI/CD, containerization, monitoring). Additionally, you should have hands-on experience with integrating systems via APIs, webhooks, and data pipelines.

In this role, you will:

• Develop, configure, deploy, and optimize AI agents using Cresta’s AI platform and tools.
• Build AI agent integrations with external systems (APIs, databases, CRMs, etc.) to ensure seamless workflow integration.
• Optimize AI agent performance (e.g. fine-tune prompts and configurations) and troubleshoot issues in complex enterprise environments.
• Collaborate with customers and internal stakeholders to gather technical requirements and translate business needs into AI Agent solutions.
• Conduct interactive demos and present compelling proof-of-concepts to prospective customers, proactively gather feedback, and iteratively refine solutions to meet objectives.
• Define project milestones, create implementation plans, and coordinate execution with internal teams to ensure on-time delivery. Provide a tight feedback loop to our product and engineering teams , identifying gaps, building custom tooling, and influencing the roadmap through real-world deployment learnings.
• Collaborate with PMs to define agent goals, iterate rapidly based on customer feedback, and shape product capabilities that maximize customer ROI.
• Serve as a trusted technical advisor for the customer, guiding best practices for AI agent adoption and usage. Provide technical guidance on AI agent best practices, including architecture design, security considerations, and scalability planning.

We offer a comprehensive and people-first benefits package to support you at work and in life:

• We offer Cresta employees a variety of medical benefits designed to fit your stage of life
• Flexible vacation time to promote a healthy work-life blend
• Paid parental leave to support you and your family

Cresta’s approach to compensation is simple: recognize impact, reward excellence, and invest in our people. We offer competitive, location-based pay that reflects the market and what each individual brings to the table.

The posted base salary range represents what we expect to pay for this role in a given location. Final offers are shaped by factors like experience, skills, education, and geography. In addition to base pay, total compensation includes equity and a comprehensive benefits package for you and your family.

XML job scraping automation by YubHub

At Cresta, the AI Agent team is on a mission to create state-of-the-art AI Agents that solve practical problems for our customers. We are focused on leveraging the latest technologies in Large Language Models (LLMs) and AI Agent systems, while ensuring that the solutions we develop are cost-effective, secure, and reliable.

As an AI Agent Engineer, you'll be at the forefront of deploying AI agents that address real-world challenges. In this role, you will work closely with customers as well as our software and machine learning engineers, ensuring high-impact AI Agent deployments and contributing to the continuous improvement of our core AI platform. You’ll develop intelligent AI agents, integrate them seamlessly with external systems and offer hands-on technical expertise to ensure successful deployments.

Responsibilities:

• Develop, configure, deploy, and optimise AI agents using Cresta’s AI platform and tools.
• Build AI agent integrations with external systems (APIs, databases, CRMs, etc.) to ensure seamless workflow integration.
• Optimise AI agent performance (e.g. fine-tune prompts and configurations) and troubleshoot issues in complex enterprise environments.
• Collaborate with customers and internal stakeholders to gather technical requirements and translate business needs into AI Agent solutions.
• Conduct interactive demos and present compelling proof-of-concepts to prospective customers, proactively gather feedback, and iteratively refine solutions to meet objectives.
• Define project milestones, create implementation plans, and coordinate execution with internal teams to ensure on-time delivery. Provide a tight feedback loop to our product and engineering teams , identifying gaps, building custom tooling, and influencing the roadmap through real-world deployment learnings.
• Collaborate with PMs to define agent goals, iterate rapidly based on customer feedback, and shape product capabilities that maximise customer ROI.
• Serve as a trusted technical advisor for the customer, guiding best practices for AI agent adoption and usage. Provide technical guidance on AI agent best practices, including architecture design, security considerations, and scalability planning.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 3+ years of full-time working experience in software development/Consulting, AI/ML engineering, or Forward Deployed Engineering.
• Proficiency in Python and Golang, with the ability to write clean, efficient code.
• Familiarity with AI/ML concepts. Hands-on experience with large language models (LLMs), and prompt engineering techniques are strongly preferred.
• Strong understanding of general AI agent frameworks, function calling, and retrieval-augmented generation (RAG). Hands-on experience of building such a system is strongly preferred.
• Experience with cloud platforms (AWS, GCP, or Azure) and DevOps practices (CI/CD, containerisation, monitoring).
• Hands-on experience with integrating systems via APIs, webhooks, and data pipelines.
• Excellent communication and project management skills.
• Ability to use data-driven decision-making, including A/B testing and performance monitoring, to refine solutions.
• Thrive in cross-functional environments, working hand-in-hand with PMs and engineers to turn real customer problems into scalable AI solutions.

Perks & Benefits:

• Comprehensive medical, dental, and vision coverage with plans to fit you and your family.
• Flexible PTO to take the time you need, when you need it.
• Paid parental leave for all new parents welcoming a new child.
• Retirement savings plan to help you plan for the future.
• Remote work setup budget to help you create a productive home office.
• Monthly wellness and communication stipend to keep you connected and balanced.
• In-office meal program and commuter benefits provided for onsite employees.

Compensation at Cresta:

• Cresta’s approach to compensation is simple: recognise impact, reward excellence, and invest in our people. We offer competitive, location-based pay that reflects the market and what each individual brings to the table.
• The posted base salary range represents what we expect to pay for this role in a given location. Final offers are shaped by factors like experience, skills, education, and geography. In addition to base pay, total compensation includes equity and a comprehensive benefits package for you and your family.
• Base Salary Range: $185,000–$235,000 + Annual Bonus & Offers Equity.

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Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the Team

The Frontier Red Team (FRT) is a small, focused technical research team within Anthropic's Policy organization. Our goal is to make the entire world safer in this era of advanced AI by understanding what these systems can do and building the defenses that matter.

In 2026, we're focused on researching and ensuring safety with self-improving, highly autonomous AI systems—especially ones with cyberphysical capabilities. See our previous related work on cyberdefense, robotics, and Project Vend. This is early-stage, high-conviction research with the potential for outsized impact.

About the Role

Our team is focused on a critical question: how do we defend against a world where powerful, autonomous, self-improving AI systems may be used adversarially?

As a Research Engineer on our team, you'll build and eval model organisms of autonomous systems and develop the defensive agents needed to counter them. This work sits at the intersection of AI capabilities research, security, and policy—what we learn directly shapes how Anthropic and the world prepare for advanced AI.

This is applied research with real-world stakes. Your work will inform decisions at the highest levels of the company, contribute to public demonstrations that shape policy discourse, and help build technical defenses that could matter enormously as AI systems become more capable.

What You'll Do

• Design and build autonomous AI systems that can use tools and operate across diverse environments—creating model organisms that help us understand and defend against advanced adversarial AI

• Create evals and training environments to understand and shape agent behavior in desirable ways

• Develop defensive agents that can detect, disrupt, or outcompete adversarial AI systems in realistic scenarios

• Interface Claude with hardware platforms (e.g. robotics, physical systems) to understand cyberphysical risks and defenses

• Translate technical findings into compelling demonstrations and artifacts that inform policymakers and the public

• Collaborate with external experts in cybersecurity, national security, and AI safety to scope and validate research directions

Sample Projects

• Developing systems where Claude controls diverse hardware and robotics platforms simultaneously

• Creating attack-defend simulations (CTFs, wargames, adversarial games) to test defensive AI capabilities

• Designing and implementing RL environments for training defensive agents

• Pointing autonomous systems at real-world security challenges to characterize risks and develop mitigations

You May Be a Good Fit If You

• Have strong software engineering skills, particularly in Python

• Have experience building and working with LLM-based agents or autonomous systems

• Are driven to find solutions to ambiguously scoped, high-stakes problems

• Design and run experiments quickly, iterating fast toward useful results

• Thrive in collaborative environments (we love pair programming!)

• Care deeply about AI safety and want your work to have real-world impact on how humanity navigates advanced AI

• Can own entire problems end-to-end, including both technical and non-technical components

• Are comfortable working on sensitive projects that require discretion and integrity

Strong Candidates May Also Have

• Experience with reinforcement learning, self-play, or multi-agent systems

• Experience with robotics, hardware interfaces, or cyberphysical systems

• Track record of building demos or prototypes that communicate complex technical ideas

• Experience working with external stakeholders (policymakers, government, researchers)

• Familiarity with AI safety research and threat modeling for advanced AI systems

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiters to help us find the best candidates for our open roles.

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What you'll do

Research & Development

• Post-train SOTA LLMs using the latest supervised and reinforcement learning techniques (SFT/DPO/GRPO)
• Leverage our rich query/answer dataset to scale model performance across Sonar, Deep Research, Comet, and Search products

What you need

• Proven experience with large-scale LLMs and Deep Learning systems

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What you'll do

You will work closely with Application Security and Red Team engineers, applying an attacker's mindset to AI systems while building scalable security testing, automation, and guardrails that meaningfully reduce risk.

• Perform security testing and reviews of AI-enabled applications, agents, and workflows, including architecture, design, and implementation analysis
• Identify and validate vulnerabilities in LLM-based systems such as data leakage, insecure tool use, authentication gaps, and abuse paths

What you need

• Strong background in application security, offensive security, or a combination of both
• Hands-on experience identifying and exploiting security weaknesses in modern applications and services

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