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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Microsoft AI are looking for a talented Member of Technical Staff - Principal Data Infrastructure Engineer at their Redmond office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.

About the Role

As a Member of Technical Staff - Principal Data Infrastructure Engineer, you will be responsible for architecting and maintaining scalable, reliable, and observable Big Data Infrastructure for mission-critical AI applications. You will champion DevOps and SRE best practices—automated deployments, service monitoring, and incident response. You will build a self-service big data platform that empowers data and platform engineers and researchers. You will develop robust CI/CD pipelines and automate infrastructure provisioning using Infrastructure as Code tools (Bicep, Terraform, ARM).

Accountabilities

• 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.

The Candidate we're looking for

Experience:

• 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.

Technical skills:

• 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.

Personal attributes:

• Excellent interpersonal and communication skills, with a solid passion for mentorship and continuous learning.

Benefits

• Starting January 26, 2026, Microsoft AI 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.
• Microsoft’s mission is to empower every person and every organization on the planet to achieve more.
• 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.

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