Top Artificial Intelligence DevOps & Platform Engineering Jobs

Build and maintain scalable multi-tenant cloud infrastructure for user applications, ensuring high reliability and performance while collaborating on innovative platform features.

The Site Reliability Engineer will manage digital infrastructure, ensuring access to compute resources, automating processes, and maintaining resource visibility for researchers.

Design, maintain, and scale core cloud infrastructure; build monitoring, observability, CI/CD pipelines, and internal tooling; prevent and troubleshoot incidents; optimize performance; and develop AI-first, agent-driven workflows to improve developer velocity and production reliability.

The Sr. DevOps Engineer will manage cloud infrastructure, ensuring efficient deployment and maintenance with extensive use of AWS and Cassandra.

The Senior / Staff Infrastructure Engineer will design and manage infrastructure for AI platforms, ensuring security, reliability, and scalability in cloud deployments. Responsibilities include deploying hybrid solutions and implementing infrastructure-as-code.

As a DevOps Engineer, you'll enhance development pipelines, automate testing, and work closely with product engineering to improve update deliveries.

The Senior Platform Engineer will design, build, and maintain cloud infrastructure, backend services, and APIs, ensuring reliability and performance.

Own and architect enterprise integrations for security ecosystems, maintain asynchronous integration services (Python with planned Rust migration), build connectors (REST, MQTT, SignalR) and webhook handlers, implement resilient pipelines with retries/backoff and monitoring, construct test harnesses for legacy hardware, lead Kubernetes migrations, collaborate with stakeholders, and act as primary incident responder for integration issues.

Build and scale backend services and integrations for autonomous AI agents. Design distributed, stateless and stateful systems, APIs, and infrastructure for reliability, security, and enterprise integration. Drive scalability, CI/CD, container orchestration, multi-cloud deployments, and mentor growing engineering teams.

Design and operate backend systems that ingest, process, store, and serve petabyte-scale video and sensor data. Build high-throughput upload/ingest, processing, indexing, retrieval, and access-control services. Own service quality, latency, uptime, capacity planning, cost, observability, and incident response. Coordinate distributed compute across cloud infrastructure and large GPU fleets to make data movement reliable and performant.