Top Artificial Intelligence DevOps & Platform Engineering Jobs

Maintain and troubleshoot an enterprise environment of approximately 800 systems and 2 petabytes of storage. Manage Linux systems, workstations, servers, networks, applications, storage, and cloud infrastructure. Configure and deploy hardware and operating systems, support users, monitor workflows, plan upgrades, coordinate outages, and participate in architecture discussions. Provide continuous operational support through a 24/7 on-call rotation.

Support secure cloud-based Linux and HPC environments for external customers using silicon design platforms. Troubleshoot compute, storage, networking, identity, scheduler, performance, and licensing issues; maintain reliability and availability; automate monitoring, provisioning, and incident response with Python, shell scripting, Perl, and agentic AI. Manage ITAR/CUI compliance, participate in root cause analysis, and create operational and customer-facing documentation.

Lead architecture and implementation for reliable, scalable AI authoring platforms. Build cloud infrastructure, CI/CD pipelines, Kubernetes and Helm deployments, infrastructure-as-code, observability, disaster recovery, A/B testing, and release processes. Improve backend reliability, performance, security, and cost efficiency across Azure and Google Cloud. Partner with product and engineering teams on technical strategy, ML infrastructure, LLM inference, and AI-assisted game development tools.

Lead cloud migration and platform engineering efforts, designing AWS architectures and migration plans from on-prem VMware to AWS. Perform migration assessments, tooling selection, wave planning, dependency analysis, security/compliance alignment, OS and database troubleshooting, and optimize post-migration performance while collaborating with stakeholders and platform teams.

Leads corporate IT and DevOps across four international sites, managing teams, SaaS applications, identity, endpoints, networking, datacenter and EDA infrastructure. Owns security, compliance, Linux systems, Kubernetes, CI/CD, developer tooling, physical IT, vendors, budgets and infrastructure modernization. Drives identity automation, OS migrations, SaaS governance, audit readiness, datacenter expansion, international integration and support for semiconductor engineering environments.

Own and improve cloud infrastructure, CI/CD pipelines, deployment tooling, monitoring, alerting, and incident response. Embed security and compliance controls for CJIS, CMMC, and SOC 2 requirements. Partner with engineering, security, product, and delivery teams to prioritize infrastructure work. Implement AI-driven DevOps automation, including remediation, anomaly detection, infrastructure-as-code generation, and compliance evidence collection.

Build and maintain reliable, scalable platforms and services. Responsibilities include monitoring, incident response, post-mortems, disaster recovery testing, production automation, AI service deployment, infrastructure documentation, and reliability testing. The role requires advanced Terraform, AWS operations, GitHub Actions CI/CD, containerized ECS Fargate environments, networking and security expertise, Linux and scripting skills, observability, and developer enablement across engineering teams.

Deploys, maintains, and scales GitLab-centered engineering platforms and tooling. Designs complex CI/CD pipelines for container, Helm, RPM, and cross-platform builds; manages artifact registries; integrates SAST, code quality, vulnerability scanning, automated testing, and security controls. Establishes development standards, branch strategies, commit conventions, code review practices, pre-commit hooks, project scaffolding, signing, and secret management. May also build machine learning specialization pipelines.

Own infrastructure for deploying and operating AI agent systems across customer environments. Responsibilities include workflow reliability, CI/CD, secrets and access controls, database performance, observability, integration resilience, incident response, and on-call operations. The role works closely with engineers to build practical shared infrastructure, investigate production failures, and improve systems across deployments. This is an in-person San Francisco position with occasional extra hours and weekend commitments.

Leads the SRE function and team, establishing reliability practices, observability standards, automation, incident management, and 24x7 operations. Develops scalable monitoring and AIOps architectures, modernizes hybrid cloud and enterprise network connectivity, and partners with infrastructure, engineering, cybersecurity, and service providers. Provides architectural guidance, drives migration and continuous improvement, and reports reliability and operational maturity to leadership.