Top Artificial Intelligence DevOps & Platform Engineering Jobs

Automates and operates enterprise AWS and public cloud infrastructure using Infrastructure as Code, scripting, source control, and DevOps workflows. Manages highly available IaaS and PaaS environments, virtualization, containers, microservices, monitoring, troubleshooting, security controls, cost optimization, and technical documentation. Partners with architects to deliver resilient cloud solutions and supports periodic after-hours maintenance. Requires strong Windows and Linux administration, networking knowledge, AI-assisted engineering skills, and at least five years of cloud engineering experience.

Build and operate secure, production-grade infrastructure across Kubernetes, commercial and government clouds, edge appliances, classified networks, and air-gapped environments. Responsibilities include platform architecture, infrastructure coding, artifact pipelines, monitoring, incident response, security hardening, CVE remediation, STIG implementation, audit readiness, and DevSecOps improvement. Collaborate with Product, Engineering, GRC, and mission teams to support reliable deployments in IL5, IL6, and JWICS environments.

Own and evolve production infrastructure for AI workloads, including Kubernetes, cloud-native migrations, scheduling, orchestration, observability, infrastructure as code, deployment workflows, security, reliability, and incident recovery. Partner with engineering and business operations teams to build dependable platform capabilities. The role requires deep production Kubernetes experience, strong cloud and Linux fundamentals, architectural judgment, automation skills, and end-to-end ownership of infrastructure systems.

Leads infrastructure, platform operations, and DevOps teams supporting a large private-cloud environment. Owns availability, performance, security, capacity, lifecycle management, 24x7 operations, incident response, automation, disaster recovery, and continual improvement. Coordinates cross-functional infrastructure programs, manages dependencies and risks, oversees ITSM processes and service metrics, and communicates technical and operational priorities to engineering and executive stakeholders.

Designs, deploys, automates, and operates secure, scalable Azure cloud platforms. Responsibilities include infrastructure as code with Terraform, AKS and container management, Azure DevOps CI/CD pipelines, cloud networking, identity and access administration, monitoring, troubleshooting, security compliance, cost optimization, and hybrid or multi-cloud connectivity. The role also administers Windows and Linux environments, supports Microsoft 365 and Active Directory, documents operational standards, collaborates across teams, and mentors others on cloud and DevOps practices.

Build and maintain machine learning applications across AWS EKS and on-premises clusters. Develop Python and FastAPI APIs, manage Kubernetes deployments, integrate databases and storage systems, maintain CI/CD pipelines, administer Linux infrastructure, troubleshoot environments, and support cloud-native observability and infrastructure-as-code practices.

Leads an integrated DevSecOps and operations delivery model for Department of Commerce OCIO environments. Oversees CI/CD, security integration, automation, monitoring, observability, incident and change management, production readiness, service transitions, and continuous improvement. Coordinates engineering, development, cybersecurity, service desk, and vendor teams while improving deployment speed, reliability, compliance, and operational efficiency.

Develop Temporal workflows and Go services to automate cloud operations, build reliable SRE platforms, participate in on-call/incident response, debug distributed systems, and enable self-service through documentation and CI/CD automation.

Own and operate the internal platform for engineering: design and run Kubernetes and bare-metal infrastructure, automate via Terraform/Ansible and scripting, build CI/CD and self-service tooling, optimise networking and storage for ML/hardware workloads, implement monitoring and security (IAM, secrets, threat detection), and drive reliability and continuous improvement.

Own and scale multi-cloud infrastructure across AWS, GCP, Cloudflare, and Hetzner. Manage Kubernetes production environments, Terraform infrastructure, observability, monitoring, CI/CD, incident response, networking, security, and cloud cost optimization. Partner with engineering teams on architecture, deployment reliability, developer experience, and AI workload infrastructure. Participate in L2 on-call rotations and lead lasting improvements to infrastructure resilience and performance.