We are seeking an experienced and innovative AI Product Engineer – Agentic Platforms to join our Financial Services Artificial Intelligence & Business Lines (FS-ABL) practice. This role is ideal for a consulting technologist with deep expertise in modern GenAI tooling, agentic system design, and enterprise SDLC, who can partner directly with clients to envision, design, develop, and deploy Agentic AI platforms in regulated environments.

In this role, you will work at the intersection of client advisory, AI product engineering, and delivery execution, helping banks, insurers, and capital markets firms transition from GenAI pilots to production-grade, governed, multi-agent systems. You will apply leading GenAI frameworks and LLM platforms , including Anthropic, OpenAI, LangChain, LangGraph, DSPy, and vector databases,while operating across the full Agentic SDLC.

P&C Insurance knowledge and experience is a significant plus. Additionally, familiarity with core insurance platforms like Guidewire, DuckCreek or Majesco will be extremely helpful to succeed in this role.

We are looking for candidates across all levels of experience and expertise - junior through senior level AI Product Engineers.

Responsibilities

Client Advisory & Product Vision

Partner directly with Financial Services clients to identify, prioritize, and shape Agentic AI use cases across customer operations, underwriting, claims, risk, compliance, finance, and technology.

Lead client workshops to define agent personas, responsibilities, autonomy boundaries, human-in-the-loop checkpoints, and escalation logic.

Translate evolving business needs into agentic product backlogs, roadmaps, and MVP definitions.

Support executive conversations around GenAI platform strategy, operating models, vendor selection, and scale-out approaches.

Agentic Platform & Architecture Design

Design and implement multi-agent architectures using modern GenAI tooling, including:

Planner, executor, reviewer/critic, and supervisor agents

Tool-calling and function-calling agents

Memory-enabled agents (conversation, semantic, episodic, and structured memory)

Leverage LangChain and LangGraph for agent orchestration, workflows, and control flow.

Apply DSPy and declarative prompt optimization techniques for repeatability, performance tuning, and regression control.

Design agent interaction patterns such as hierarchical agents, collaborating agents, and event-driven agent workflows.

Define standardized agent contracts, interfaces, and schemas to enable reuse and scale.

Agentic SDLC & Engineering Delivery

Own delivery across the full Software Development Lifecycle (SDLC), extending it into a formal Agentic SDLC, including:

Agent design specifications and behavior contracts

Prompt, policy, and tool versioning

Simulation environments and offline evaluation

Automated testing of agent flows and guardrails

Controlled rollout, telemetry-driven optimization, and continuous learning

Build production-grade AI services primarily using Python, integrating:

LLM providers such as Anthropic (Claude), OpenAI, and open-source models

Retrieval-Augmented Generation (RAG) using vector databases (e.g., Pinecone, FAISS, Milvus, Weaviate)

Implement CI/CD pipelines for agent code, prompts, and policies.

Integrate GenAI agents with client systems via APIs, workflow engines, event streams, and data platforms.

Observability, Evaluation & Optimization

Implement agent observability including tracing, decision logging, tool usage, and failure analysis.

Apply evaluation frameworks for hallucination detection, consistency checks, and fitness scoring.

Design feedback loops incorporating human-in-the-loop review and reinforcement.

Monitor cost, latency, throughput, and behavioral drift across deployed agents.

Governance, Risk & Financial Services Compliance

Design Agentic AI platforms aligned with Financial Services regulatory expectations, including:

Auditability and traceability of agent decisions

Model and prompt explainability

Data privacy and security controls

Resilience and fail-safe mechanisms

Embed guardrails and policies addressing hallucination risk, bias, unauthorized actions, and escalation failures.

Produce documentation supporting risk, compliance, internal audit, and regulator engagement.

Team Leadership & Firm Contribution

Provide technical leadership and mentorship to consulting delivery teams.

Contribute to internal GenAI accelerators, agent frameworks, and reusable assets.

Support RFPs, proposals, and client solution designs with credible GenAI and agentic architectures.

Participate in thought leadership on Agentic SDLC, GenAI engineering, and responsible autonomy.

Benefits

This position comes with competitive compensation and benefits package:

1. Competitive salary and performance-based bonuses

1. Comprehensive benefits package

1. Career development and training opportunities

1. Flexible work arrangements (remote and/or office-based)

1. Dynamic and inclusive work culture within a globally known group

1. Private Health Insurance

1. Retirement Benefits

1. Paid Time Off

1. Training & Development

1. Note: Benefits differ based on employee level

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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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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. You’ll contribute to designing and building AI-powered defenses, secure orchestration frameworks, and enabling technologies that empower Copilot to act safely and responsibly at scale. This role is ideal for engineers who are passionate about applying technical skills to solve security challenges and build systems that balance innovation with trust.

Why This Role Matters 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.

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 Ability to clearly explain complex systems and security concepts to technical and non-technical stakeholders and influence cross-org roadmaps. 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

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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.

Responsibilities:

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:

Required 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.

Preferred Qualifications:

Master’s Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor’s Degree in Computer Science or related technical field AND 12+ 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.

XML job scraping automation by YubHub

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.

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

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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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As Director of Enterprise ML, you will lead a world-class team of research scientists and engineers, define the research roadmap, and drive execution from early prototyping to deployment. You’ll thrive in a fast-moving environment, balancing deep technical leadership with people management, vision setting, and delivery.

This role is ideal for a leader who thrives in ambiguity, understands both frontier GenAI capabilities and their limitations, and is motivated by turning research into durable, production-ready systems.

Key responsibilities include:

• Leading, mentoring, and growing a team of research scientists and engineers working on GenAI research initiatives
• Defining and driving a multi-year research roadmap, identifying key scientific questions, setting milestones, allocating resources, and ensuring rigorous execution
• Collaborating cross-functionally with engineering, product, client-facing teams, and external academic or industry partners to translate research into components, insights, and actionable outcomes
• Communicating compellingly, publishing research, presenting at conferences, engaging in open-source contributions, and representing the team externally
• Driving an inclusive, high-performing culture, helping your team through technical challenges, providing growth opportunities, and attracting top talent

Core qualifications include:

• 8+ years of hands-on research experience in machine learning, deep learning, generative models, agent/RL systems, or related domains
• A strong track record of research excellence, including publications in top-tier ML/AI venues
• Experience leading or managing research teams
• Excellent written and verbal communication skills

Nice-to-have qualifications include:

• Hands-on experience building and deploying agent-based, tool-augmented, or workflow-driven LLM systems in enterprise environments
• Prior ownership of enterprise AI platforms, internal ML products, or customer-facing AI services at scale
• Proven track record of partnering directly with enterprises to identify high-impact use cases and deliver measurable business outcomes

Compensation packages at Scale include base salary, equity, and benefits, with a salary range of $289,800-$362,250 USD for this full-time position in San Francisco, New York, and Seattle.

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Your responsibilities will include:

• Designing extensible, production-grade services that can support frontier AI workflows, including multi-modal inputs, long-running processes, and agentic orchestration.
• Building and operating distributed systems at scale, with strong guarantees around correctness, reliability, observability, and cost efficiency.
• Integrating with public LLM APIs and AI services, designing abstractions that are resilient to model churn, latency variability, and evolving usage patterns.
• Designing and maintaining data transformation and processing systems, supporting complex schema evolution, customization, and high-throughput workloads.
• Partnering closely with infrastructure, product, and customer-facing teams to define requirements, shape technical direction, and deliver seamless integration experiences for customers.
• Leading multi-quarter technical initiatives, including authoring and driving a 6+ month technical roadmap for major platform investments.
• Applying strong engineering judgment in ambiguous problem spaces, balancing speed with long-term maintainability and operational excellence.
• Raising the quality bar through thoughtful system design reviews, rigorous code reviews, and mentorship grounded in real-world production experience.

Ideal Experience:

• 7+ years of professional software engineering experience, with a strong background in building and operating large-scale, production-grade platforms.
• Deep expertise in distributed systems and cloud-native architectures, including Kubernetes, microservices, event-driven systems, caching, and production databases.
• Proven ability to lead multi-quarter technical initiatives, work effectively across cross-functional teams, and apply strong architectural judgment in ambiguous environments.

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.

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San Francisco

Employment Type

Full time

Department

Consumer Products

Compensation

• $293K – $325K • Offers Equity

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.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

The Software Engineering team is responsible for designing and building the scalable, performant, and secure backend systems that power our products—from early prototypes to large-scale deployments. We collaborate closely with product, hardware, and full-stack teams to ensure our infrastructure enables fast iteration while setting a strong foundation for long-term growth.

About the Role

As a Backend Engineer, you will design and build services, APIs, and infrastructure that support evolving product needs. You’ll apply a deep understanding of backend systems and maintain enough end-to-end context—from hardware to cloud—to guide technical decisions that best serve the product and team.

We’re looking for engineers who thrive in fast-paced, collaborative environments and care deeply about building robust systems that scale.

This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Architect, build, and maintain high-performance, secure backend systems.
• Design APIs, data models, and infrastructure to support evolving product needs.
• Balance near-term development velocity with long-term maintainability and scalability.
• Collaborate with cross-functional teams to ensure cohesive, end-to-end solutions.

You might thrive in this role if you:

• Have 7+ years of professional software engineering experience, with a focus on backend systems.
• Have a proven track record of building and scaling systems from early stage to large scale.
• Are proficient with Python and Go, and familiar with a range of server-side technologies.
• Have a strong grasp of system design, performance optimization, and security best practices.
• Can reason about full-stack tradeoffs from hardware through cloud infrastructure.
• _(Nice to have)_ Have experience with distributed systems and cloud architectures.
• _(Nice to have)_ Bring a background in instrumentation, analytics, and performance tuning.
• _(Nice to have)_ Are familiar with hardware-cloud integrations or applied AI services.

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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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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