Designs, builds, and operates cloud infrastructure, deployment, observability, and reliability systems. Responsibilities include infrastructure-as-code, Kubernetes, CI/CD, incident response, SLOs, cost optimization, automation, and production readiness across cloud, hybrid, edge, and customer-controlled environments. The role improves platform stability, delivery speed, operational efficiency, and reliability for mission-critical systems.

Designs, builds, deploys, monitors, and supports backend services powering an enterprise AI platform. Responsibilities include developing APIs, AI gateway and orchestration capabilities, multi-tenant systems, entitlements, metering, integrations, data access patterns, and platform services. The engineer owns services end to end while addressing reliability, distributed-system failure modes, testing, operational support, and developer experience.

Build and operate production AI capabilities across enterprise platforms, including agent runtimes, RAG, model routing, tool calling, guardrails, evaluation, monitoring, and cost and latency optimization. Ship reliable, measurable, safe AI features, develop evaluation frameworks, monitor production behavior, and collaborate with backend, platform, product, security, and client teams.