Lead Python Developer

We are seeking a Lead Python Developer to drive technical direction and hands-on development within our pod, focusing on backend AI services, LLM orchestration and agentic experiences. You will write production code, mentor engineers, and collaborate cross-functionally with Security, Data and Infrastructure teams while partnering with US-based product and engineering counterparts. This role blends embedded leadership with deep technical ownership, ensuring observability, reliability and operational excellence across pod services.

Set technical direction for the pod and own architecture decisions within scope Write production code (~50%+ of the time) across backend AI services, LLM orchestration and frontend integration Design and build Agentic Experiences (AX) with streaming, low-latency agent UIs Mentor 3 Senior Engineers and 1 Data Engineer within the pod Partner with Security, Data and Infrastructure teams on daily collaboration Align with US-based product and engineering counterparts Conduct design reviews and unblock sprint deliverables Enforce observability, SLOs and reliability standards for pod services 5+ years of software engineering experience with a track record of owning complex backend systems end-to-end 1–2+ years on LLM-era AI/ML platforms such as LangChain, LangGraph or Bedrock in a production context; candidates with deeper pre-LLM ML backgrounds (TensorFlow, scikit-learn) who have made a clear and recent pivot to generative AI will also be considered Expert-level proficiency in Python for backend services and AI integration as the primary language for all backend and AI work Hands-on expertise in LangChain, LangGraph and LangSmith for orchestrating multi-step, multi-agent workflows and evaluation/observability Proven background in AWS, Docker and microservices at production scale Skills in GitHub Actions, ArgoCD and OpenTofu/Terraform Competency in secure coding practices, auth/authz awareness and data governance as default standards Expertise in API design including RESTful APIs and microservices English proficiency at B2 level or higher Fluency in React and TypeScript with the capability to contribute to UI-layer code and review frontend work Familiarity with MCP (Model Context Protocol) and emerging agent interoperability standards Knowledge of AI evaluation tooling such as RAGAS or custom eval frameworks Background in designing and optimizing RAG pipelines with vector databases (Amazon Kendra, OpenSearch) Understanding of identity/security domains (IAM, CIAM) and handling unstructured data (images, videos) with prompt context management via LangGraph State