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 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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As a Technical Program Manager on the Marketplace Management team, you will own critical components of this ecosystem, driving product capabilities, partner integrations, and marketplace health initiatives that shape the future of Microsoft Ads.

The role requires deep analytical judgment to evaluate publisher-level and ecosystem-level performance, identify structural opportunities, and influence long-term marketplace direction. This role demands exceptional cross-functional leadership, driving alignment and decisions across Microsoft Advertising, Engineering.

Success requires strong executive-level communication, the ability to navigate ambiguity, and a partner-obsessed mindset with a track record of solving complex, systemic problems and translating them into scalable marketplace solutions.

Manage the end-to-end lifecycle of marketplace capabilities for Search publishers, including defining requirements, prioritizing features, and driving execution across engineering teams.

Lead the delivery of new marketplace features and enhancements that improve partner performance, system efficiency, and advertiser outcomes.

Ensure marketplace configurations, policies, and controls are aligned with business goals and partner commitments.

Drive strategic discussions with Search publishers to understand their marketplace commitments, identify gaps, and align on improvements that strengthen the ecosystem.

Continuously analyze marketplace health metrics, including traffic quality, revenue performance, discrepancy trends, and partner-specific signals.

Investigate anomalies or discrepancies, synthesize insights, and recommend corrective actions to internal teams and external partners.

Build frameworks, dashboards, and processes that improve visibility into marketplace performance and enable proactive issue detection.

Collaborate closely with engineering, data science, product management, and business development to deliver high-impact marketplace improvements.

Drive alignment across teams by articulating problem statements, defining success metrics, and ensuring timely execution of deliverables.

Manage program risks, dependencies, and communication plans to keep stakeholders informed and accountable.

Qualifications:

Bachelor’s Degree AND 6+ years experience in engineering, product/technical program management, data analysis, or product development OR equivalent experience.

3+ years of experience managing cross-functional and/or cross-team projects.

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.

These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred Qualifications:

Bachelor’s Degree AND 12+ years experience engineering, product/technical program management, data analysis, or product development OR equivalent experience.

8+ years of experience managing cross-functional and/or cross-team projects.

Proficient use of data analysis tools (e.g., Kusto, SQL, Python) and comfort working with large datasets.

#MicrosoftAI #Ads #Advertising #A/BTesting #Experimentation

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We’re looking for a Member of Technical Staff – Principal Data Infrastructure Engineer. This role is a dynamic blend of Platform Engineering, DevOps/SRE, and Big Data Infrastructure Engineering, focused on enabling large-scale data and ML pipelines and intelligent systems. If you’ve architected big data platforms from the ground up and are eager to apply that expertise to consumer AI, we want to hear from you.

You’ll bring:

Deep technical expertise A passion for automation and observability Fluency in distributed systems Creativity to design scalable solutions And just as importantly: 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:

Architect and maintain scalable, reliable, and observable Big Data Infrastructure for mission-critical AI applications. Champion DevOps and SRE best practices,automated deployments, service monitoring, and incident response. Build a self-service big data platform that empowers data and platform engineers and researchers. Develop robust CI/CD pipelines and automate infrastructure provisioning using Infrastructure as Code tools (Bicep, Terraform, ARM). Collaborate with Data Engineers, Data Scientists, AI Researchers, and Developers to deliver secure, seamless big data workflows. Lead technical design reviews and uphold a clean, secure, and well-documented codebase. Proactively identify and resolve bottlenecks in data pipelines and infrastructure. Optimize system performance across storage, compute, and analytics layers. Partner with Security teams to enhance system security (IAM, OAuth, Kerberos). Embody and promote Microsoft’s values: Respect, Integrity, Accountability, and Inclusion.

Qualifications:

Required Qualifications: 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, data modeling, or data engineering OR 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 OR equivalent experience.

Preferred Qualifications: 4+ years in Big Data Infrastructure, DevOps, SRE, or Platform Engineering. 3+ years of hands-on experience managing and scaling distributed systems,from bare-metal to cloud-native environments. 2+ years deploying containerized applications using Kubernetes and Helm/Kustomize. Solid scripting and automation skills using Python, Bash, or PowerShell. Proven success in CI/CD pipeline management, release automation, and production troubleshooting. Experience working with Databricks for scalable data processing and analytics. Familiarity with security practices in infrastructure environments, including IAM, OAuth, and Kerberos administration. Proven experience with cloud-native infrastructure across Azure, AWS, or GCP. Hands-on expertise with modern data platforms like Databricks, including: Deep understanding of data storage and processing technologies: Relational & NoSQL databases Key-value stores. Spark compute engines. Distributed file systems (e.g., HDFS, ADLS Gen2). Messaging systems (e.g., Event Hub, Kafka, RabbitMQ). Capacity planning and incident management for large-scale big data systems. Solid collaboration history with Data Engineers, Data Scientists, ML Engineers, Networking, and Security teams. Familiarity with modern web stacks: TypeScript, Node.js, React, and optionally PHP. Exposure to agentic workflows, deep learning, or AI frameworks. Practical experience integrating LLMs (e.g., GPT-based models) into daily workflows,automating documentation, code generation, reviews, and operational intelligence. Solid grasp of prompt engineering techniques to design, optimize, and evaluate interactions with LLMs. Demonstrated ability to troubleshoot and resolve complex performance and scalability issues across infrastructure layers. Excellent interpersonal and communication skills, with a solid passion for mentorship and continuous learning. Experience applying LLMs to DevOps workflows, enhancing incident response, and streamlining cross-functional collaboration is a solid advantage.

#MicrosoftAI #mai-datainsights #mai-datainsights

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As a Technical Program Manager on the Marketplace Management team, you will own critical components of this ecosystem, driving product capabilities, partner integrations, and marketplace health initiatives that shape the future of Microsoft Ads.

The role requires deep analytical judgment to evaluate publisher-level and ecosystem-level performance, identify structural opportunities, and influence long-term marketplace direction. This role demands exceptional cross-functional leadership, driving alignment and decisions across Microsoft Advertising, Engineering.

Success requires strong executive-level communication, the ability to navigate ambiguity, and a partner-obsessed mindset with a track record of solving complex, systemic problems and translating them into scalable marketplace solutions.

Manage the end-to-end lifecycle of marketplace capabilities for Search publishers, including defining requirements, prioritizing features, and driving execution across engineering teams.

Lead the delivery of new marketplace features and enhancements that improve partner performance, system efficiency, and advertiser outcomes.

Ensure marketplace configurations, policies, and controls are aligned with business goals and partner commitments.

Drive strategic discussions with Search publishers to understand their marketplace commitments, identify gaps, and align on improvements that strengthen the ecosystem.

Continuously analyze marketplace health metrics, including traffic quality, revenue performance, discrepancy trends, and partner-specific signals.

Investigate anomalies or discrepancies, synthesize insights, and recommend corrective actions to internal teams and external partners.

Build frameworks, dashboards, and processes that improve visibility into marketplace performance and enable proactive issue detection.

Collaborate closely with engineering, data science, product management, and business development to deliver high-impact marketplace improvements.

Drive alignment across teams by articulating problem statements, defining success metrics, and ensuring timely execution of deliverables.

Manage program risks, dependencies, and communication plans to keep stakeholders informed and accountable.

Qualifications:

Bachelor’s Degree AND 6+ years experience in engineering, product/technical program management, data analysis, or product development OR equivalent experience.

3+ years of experience managing cross-functional and/or cross-team projects.

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.

These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred Qualifications:

Bachelor’s Degree AND 12+ years experience engineering, product/technical program management, data analysis, or product development OR equivalent experience.

8+ years of experience managing cross-functional and/or cross-team projects.

Proficient use of data analysis tools (e.g., Kusto, SQL, Python) and comfort working with large datasets.

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You will partner with engineers to build dev tools that empower developer workflows and deployment infrastructure.

Ensure reliability of multi-cloud Kubernetes clusters and pipelines.

Metrics, logging, analytics, and alerting for performance and security across all endpoints and applications.

Infrastructure-as-code deployment tooling and supporting services on multiple cloud providers.

Automate operations and engineering.

Focus on automation so we can spend energy where it matters.

Building machine learning infrastructure that enables AI teams to train, test, and deploy on large-scale datasets.

We are looking for a highly skilled engineer with 5+ years of experience in DevOps, Site Reliability Engineering, Production Engineering, or equivalent field.

Deep proficiency with coding languages such as Golang or Python.

Deep familiarity with container-related security best practices.

Production experience working with Kubernetes, and a deep understanding of the Kubernetes ecosystem, including popular open-source tooling such as cert-manager or external-dns.

Experience with GPU-enabled clusters is a bonus.

Production experience with Kubernetes templating tools such as Helm or Kustomize.

Production experience with IAC tools such as Terraform or CloudFormation.

Production experience working with AWS and services such as IAM, S3, EC2, and EKS.

Production experience with other cloud providers such as Google Cloud and Azure is a bonus.

Production experience with database software such as PostgreSQL.

Experience with GitOps tooling such as Flux or Argo.

Experience with CI/CD such as GitHub Actions.

Perks and benefits include paid parental leave, monthly health and wellness allowance, and PTO.

Compensation includes a base salary, equity, and a variety of benefits.

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As a collaborative but highly autonomous working environment, each member has a defined role with clear expectations, as well as the freedom to pursue projects they find interesting.

Responsibilities:

• Partner with engineers to build dev tools that empower developer workflows and deployment infrastructure.
• Ensure reliability of multi-cloud Kubernetes clusters and pipelines.
• Metrics, logging, analytics, and alerting for performance and security across all endpoints and applications.
• Infrastructure-as-code deployment tooling and supporting services on multiple cloud providers.
• Automate operations and engineering. Focus on automation so we can spend energy where it matters.
• Building machine learning infrastructure that enables AI teams to train, test, and deploy on large-scale datasets.

What we are looking for:

• 5+ years experience in DevOps, Site Reliability Engineering, Production Engineering, or equivalent field.
• Deep proficiency with coding languages such as Golang or Python.
• Deep familiarity with container-related security best practices.
• Production experience working with Kubernetes, and a deep understanding of the Kubernetes ecosystem, including popular open-source tooling such as cert-manager or external-dns.
• Experience with GPU-enabled clusters is a bonus.
• Production experience with Kubernetes templating tools such as Helm or Kustomize.
• Production experience with IAC tools such as Terraform or CloudFormation.
• Production experience working with AWS and services such as IAM, S3, EC2, and EKS.
• Production experience with other cloud providers such as Google Cloud and Azure is a bonus.
• Production experience with database software such as PostgreSQL.
• Experience with GitOps tooling such as Flux or Argo.
• Experience with CI/CD such as GitHub Actions.

Perks & Benefits:

• 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.

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.

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You will partner with engineers to build dev tools that empower developer workflows and deployment infrastructure. You will ensure the reliability of multi-cloud Kubernetes clusters and pipelines. You will also implement metrics, logging, analytics, and alerting for performance and security across all endpoints and applications.

You will focus on automation so we can spend energy where it matters. You will build machine learning infrastructure that enables AI teams to train, test, and deploy on large-scale datasets.

We're looking for someone with 5+ years of experience in DevOps, Site Reliability Engineering, Production Engineering, or equivalent field. You should have deep proficiency with coding languages such as Golang or Python. You should also have deep familiarity with container-related security best practices.

Production experience working with Kubernetes, and a deep understanding of the Kubernetes ecosystem, including popular open-source tooling such as cert-manager or external-dns, is required. Experience with GPU-enabled clusters is a bonus.

Production experience with Kubernetes templating tools such as Helm or Kustomize, and production experience working with IAC tools such as Terraform or CloudFormation, is a plus.

Production experience working with AWS and services such as IAM, S3, EC2, and EKS, and production experience with other cloud providers such as Google Cloud and Azure, is a bonus.

Experience with GitOps tooling such as Flux or Argo, and experience with CI/CD such as GitHub Actions, is a plus.

Compensation for this position includes a base salary, equity, and a variety of benefits.

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Cyngn is a publicly-traded autonomous technology company that deploys self-driving industrial vehicles to factories, warehouses, and other facilities throughout North America.

We are a small company with under 100 employees, operating with the energy of a startup. However, we're also publicly traded, which means our employees get access to the liquidity of our publicly-traded equity.

As a Senior DevOps Lead at Cyngn, you will play a vital role in architecting and managing infrastructure across cloud and autonomous vehicle systems. This position combines traditional cloud DevOps leadership with specialized expertise in robotics and autonomous systems infrastructure.

Responsibilities

• Lead and architect cloud and vehicle infrastructure initiatives across AWS and ROS/Linux environments
• Design and implement scalable solutions for both cloud services and autonomous vehicle systems
• Establish and maintain DevOps best practices, CI/CD pipelines, and infrastructure as code
• Drive observability, monitoring, and incident response strategies
• Optimize performance and cost efficiency of cloud and edge computing resources
• Mentor team members and foster a developer-friendly environment
• Manage on-call rotations and incident response processes
• Architect solutions for processing and storing large-scale vehicle telemetry data
• Lead security initiatives and compliance efforts across infrastructure

Requirements

• 10+ years of relevant DevOps/Infrastructure experience
• Proven track record as a technical lead in platform or infrastructure teams
• Advanced expertise in AWS services, infrastructure as code (Terraform), and Kubernetes
• Strong experience with service mesh (Istio) and Helm/Kustomize
• Deep understanding of ROS/ROS2 and Linux kernel configurations
• Experience with GPU configurations and ML infrastructure
• Expertise in ARM and NVIDIA CUDA platform configurations
• Strong programming skills in Python and shell scripting
• Experience with infrastructure automation (Ansible)
• Expertise in CI/CD tools (Jenkins, GitHub Actions)
• Strong system architecture and design skills
• Excellence in technical documentation
• Outstanding problem-solving abilities
• Strong leadership and mentoring capabilities

Nice to haves

• Experience with autonomous vehicle systems
• Track record of optimizing GPU-based ML infrastructure
• Experience with large-scale IoT deployments
• Contributions to open-source projects
• Experience with real-time systems and low-latency requirements
• Expertise in security implementations including SSO, IdP, and AWS Cognito
• Experience with JFrog artifactory and container registry management
• Proficiency in AWS IoT Greengrass
• Experience with container resource management on edge devices
• Understanding of CPU affinity and priority scheduling
• Track record of implementing cost optimization strategies
• Experience with scaling systems both horizontally and vertically

Benefits & Perks

• Health benefits (Medical, Dental, Vision, HSA and FSA (Health & Dependent Daycare), Employee Assistance Program, 1:1 Health Concierge)
• Life, Short-term, and long-term disability insurance (Cyngn funds 100% of premiums)
• Company 401(k)
• Commuter Benefits
• Flexible vacation policy
• Sabbatical leave opportunity after five years with the company
• Paid Parental Leave
• Daily lunches for in-office employees
• Monthly meal and tech allowances for remote employees

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