Senior Engineer

• 7+ years’ experience in cloud and distributed systems architecture focused on scalability, reliability, observability, and performance. • 5+ years designing enterprise AI/ML systems; 1+ years hands-on with GenAI, agentic workflows, RAG, LLM-based integrations, or multi-agent systems. • Strong expertise with agentic frameworks and tooling (MCP, LangChain, LangGraph,LlamaIndex, autogen, crewai, Agent sdk,OpenAI SDK etc). • Hands-on experience in modern software development and engineering practices. • Proven experience integrating APIs and enterprise systems into agentic platforms and workflows. • Ability to rapidly build AI-driven prototypes, proofs of concept, and demo-ready product experiences. • Experience defining and governing enterprise architecture standards, patterns, and reference architectures. • Deep understanding of MCP servers, tool calling, registries, eval pipelines, agent observability, and multi-agent orchestration. • Hands-on experience with Azure and GCP, including Kubernetes, containerization, identity, networking, CI/CD, and API platforms. • Familiarity with AIOps/MLOps stacks (MLflow, model registries, vector DBs, semantic layers, feature stores, monitoring). • Strong knowledge of security, compliance, risk, and Responsible AI (RAI) considerations for enterprise agent systems. • Demonstrated ability to partner across engineering, data science, product, and security teams to deliver complex AI platform architectures.