Designs, builds, and operates cloud infrastructure, deployment systems, observability, and reliability capabilities. Responsibilities include infrastructure as code, Kubernetes, CI/CD, incident response, SLOs, cost optimization, automation, production readiness, and support for hybrid, edge, on-premises, and customer-controlled environments.

Designs, builds, deploys, operates, and supports backend services powering an enterprise AI platform. Responsibilities include developing APIs, orchestration, entitlements, tenancy, data access, integration frameworks, connectors, metering, and platform services. The role requires expertise in distributed systems, reliability, failure handling, multi-tenant architecture, testing, monitoring, and service ownership, along with strong communication and collaboration in a client-facing consulting environment.

Build and operate production AI capabilities, including agent runtimes, model routing, RAG, tool calling, guardrails, evaluation, monitoring, and cost and latency optimization. Develop reliable, measurable, safe AI systems; create evaluation harnesses and quality controls; monitor production behavior; and collaborate with backend, platform, product, and security teams in a client-facing consulting environment.