Responsibilities :

- Design, build and deploy production AI systems using Agentic AI, RAG, orchestration, tool/function calling and multi-step workflows.

- Own end-to-end customer delivery from discovery and solution architecture through deployment, rollout, iteration and operational readiness.

- Operationalize AI systems for scale by establishing evaluation, monitoring and deployment frameworks and implementing reliability patterns such as retries, fallbacks, idempotency and safe failure modes.

- Partner with AI Engineers, Platform and Research teams to translate real-world customer requirements into scalable solutions and provide deployment feedback to strengthen AI platforms.

- Drive customer and executive engagement by communicating architecture, risks, trade-offs, scope, reliability, speed and cost clearly while ensuring successful transition to long-term operational ownership.

Requirements :

- 5+ years of experience in software engineering, architecture or technical delivery, with a strong track record of shipping production systems.

- Demonstrated experience in customer-embedded delivery, taking enterprise solutions from discovery through deployment.

- Strong hands-on experience in backend and integration engineering, including APIs, services, data integrations and production debugging.

- Experience building LLM applications using RAG, tool calling, orchestration and evaluation/quality gates.

- Strong experience with production deployment practices and cloud environments, including CI/CD, containers, AWS/Azure/GCP, along with security and privacy fundamentals.