• Lead a small team covering frontend, backend and QA, including sprint execution, technical direction, code reviews and mentorship. • Own the agentic orchestration layer in Python (LangChain or similar): routing, tool-calling, state/memory, guardrails and prompt/configuration management. • Build and maintain backend services/APIs that connect UI → orchestration layer → graph database (queried via SPARQL) → retrieval (Graph RAG) → LLM. • Implement Graph RAG patterns: entity linking, context assembly, grounding/citations and response formatting for consumption in the UI. • Deliver reporting features in the UI based on the agentic framework, such as: conversation summaries, task results and traceability to evidence in the graph, latency, token/cost signals, retrieval hits and error rates. • Partner with ontology/graph engineers to ensure correct query patterns, performance tuning and schema alignment. • Establish engineering standards: structured logging, telemetry, exception handling, secure secrets management and performance optimization. • Ensure MVP quality: testing strategy, automated tests where feasible (unit/integration) and release readiness. • Responsible for containerized deployment: packaging services in Docker, supporting CI/CD, promoting between environments and implementing rollback practices in Azure.

• Design and develop modern full-stack applications and distributed systems • Build backend services using Python (including frameworks such as FastAPI) and Go • Develop frontend interfaces using React and modern JavaScript frameworks • Deploy and operate applications in containerized and Kubernetes-based environments • Rapidly prototype and validate new platform capabilities • Contribute to architecture and system design discussions • Build scalable APIs and services supporting evolving platform needs • Use modern engineering tooling, including AI-assisted development tools, to accelerate development • Collaborate with engineers and technical leadership to move concepts into production-quality systems

• Develop and maintain backend services using **Python and FastAPI** • Build and optimize APIs that power AI-driven travel planning features • Collaborate with engineers through **high-quality GitHub pull requests and code reviews** • Contribute to **sprint planning and agile development cycles** • Work on frontend components using **React** • Integrate backend systems with **MongoDB databases and AWS infrastructure** • Ensure code follows **clean architecture principles and coding standards** • Improve system performance, reliability, and scalability • Collaborate with AI and product teams to implement new platform capabilities

• Guide the design and implementation of a new LLVM based backend JIT compiler targeting NVIDIA GPUs • Design and develop new compiler passes and optimizations required to meet the high performance and low compilation time requirements of the compiler • Work with global compiler, hardware and application teams to oversee improvements and problem resolutions • Apply and adapt the latest compiler technologies to produce premier, robust, supportable compiler and tools • Get a chance to influence and work on new GPU architectures