Top Artificial Intelligence DevOps & Platform Engineering Jobs

Develop and deploy DevSecOps capabilities for defense-focused prototype systems. Responsibilities include containerizing Python applications, deploying workloads to Kubernetes, building CI pipelines and developer tooling, delivering infrastructure as code, troubleshooting Linux networking and storage, supporting cloud-native applications, and ensuring compliance with NIST, CMMC, and CIS controls.

Build and maintain scalable infrastructure platforms supporting domestic and international workloads. Develop CI/CD, declarative lifecycle management, Kubernetes clusters, monitoring, and automation systems. Troubleshoot infrastructure issues, respond to alerts, minimize downtime, streamline delivery pipelines and database changes, and help guide SRE team direction. Collaborate with engineers, data scientists, and technology professionals while promoting a high-performance, cross-functional culture.

Lead and grow an infrastructure engineering team while designing, deploying, securing, and maintaining networks, containerized services, Linux systems, workstations, backup systems, and recovery procedures. The role owns foundational architecture, documentation, availability, connectivity support, and secure workflows in a security-sensitive environment. Responsibilities also include hiring, mentoring, incident support, stakeholder collaboration, and administration of custom or potentially air-gapped infrastructure.

Design, build, and maintain infrastructure for scaling machine-learning inference across more than 150 biological models. Responsibilities include orchestrating containerized workloads with Kubernetes, optimizing resource allocation, supporting GPU workloads, ensuring high availability, and scaling AWS infrastructure. The role requires collaboration with founders and engineering teams in a fast-paced onsite startup environment, with involvement across DevOps, MLOps, cloud systems, automation, monitoring, and computational biology technologies.

Develop and maintain infrastructure for rapid software prototyping and deployment across cloud, private cloud, and bare-metal environments. Manage servers and Kubernetes clusters, configure GPU systems for large language models, optimize performance, build monitoring and alerting, and advise on localized data-center deployments. The role also requires software engineering, Linux administration, security awareness, automation, and collaboration across international teams.

Own the architecture, reliability, scalability, and developer experience of a Kubernetes-based platform supporting secure enterprise workloads. Design resilient infrastructure, define SLOs, improve observability and operational workflows, and build self-service deployment and developer tooling. Partner with product engineering and leadership to establish technical standards, resolve architectural risks, and scale infrastructure for significant customer growth.

Engineer and administer enterprise Microsoft 365 services while building scalable PowerShell, Power Automate, Microsoft Graph, and Copilot agent solutions. Responsibilities include platform governance, security, compliance, automation, service rollouts, monitoring, troubleshooting, documentation, and operational support across Teams, SharePoint, OneDrive, Entra ID, Purview, and Copilot. The role partners with security, identity, compliance, networking, endpoint, architecture, and operations teams and provides technical guidance for reliable, secure Microsoft 365 services.

Administer, configure, and support JD Edwards EnterpriseOne CNC environments, including architecture, security, performance tuning, integrations, upgrades, deployments, and lifecycle management. Manage incidents and changes using ITIL, ensure high availability and disaster recovery, troubleshoot complex issues, lead CNC projects, collaborate with infrastructure and database teams, and mentor team members. The role requires 24/7 operational support, including occasional night, weekend, and holiday shifts.

Deploy and support distributed SaaS and on-premise infrastructure, gather customer requirements, adapt deployment manifests, monitor platform health, troubleshoot issues, package releases, and automate release pipelines across Kubernetes and AWS, GCP, and Azure environments.

Lead the technical vision and architecture for Anyscale’s platform infrastructure, including control and data planes that orchestrate Ray clusters across cloud and on-premises environments. Design scalable distributed systems, establish reliability and observability standards, guide Kubernetes and container infrastructure, integrate GPUs and TPUs, resolve technical debt, mentor engineers, and influence cross-functional technical strategy.