Lead architecture and delivery of cloud micro-services in Python with LangChain, LangGraph, ADK, MCP, A2A and web-first frameworks such as FastAPI, Streamlit, Gradio, FastHTML. Own GenAI initiatives end-to-end—data strategy, model selection or fine-tuning, evaluation, deployment, and continuous optimization for structured reasoning, autonomous planning, image/video generation, and real-time “live-mode” interactions. Set engineering standards for reliability, security, performance, CI/CD, and observability; enforce them through rigorous code reviews and mentoring. Drive cross-functional execution—scope epics with product, align roadmaps, and deliver high-value features on time while proactively mitigating risk. Champion production excellence—define SLOs, monitor telemetry, lead incident response, and run blameless root-cause analyses in a true DevOps model. Mentor and multiply talent—coach engineers, run lightning talks, and foster a culture of candid feedback and continuous learning. Document and broadcast decisions through clear design docs and architecture reviews that scale knowledge across the organization. Bachelor's degree in CS, Engineering, or equivalent practical experience (Master's preferred). 6+ years of professional Python development, including large-scale, production AI/ML systems. Demonstrated experience in building applications on foundation-model APIs and to use AI daily in your workflow (GitHub Copilot, Windsurf/Cursor, Claude Code, etc.). Hands-on cloud experience (GCP, AWS, or Azure) plus containerisation (Docker, Kubernetes) and modern CI/CD pipelines. Demonstrated leadership in setting technical direction and mentoring engineers. Deep expertise with LangChain, LangGraph, ADK, MCP, A2A and multimodal model orchestration. Experience in Next-gen AI coding agents/IDEs such as Cursor, Windsurf, Claude Code. Knowledge of GCP services (Vertex AI, BigQuery, GKE, Kubeflow), Terraform, GitHub Actions, Docker, Kubernetes. Knowledge of Vector, SQL, and NoSQL data stores; streaming frameworks; distributed-systems concepts; advanced observability and SRE practices. A self-starter who devours research papers and turns them into production-ready prototypes. Energized by ambiguity and full ownership in an AI-first culture; you instinctively raise the bar for those around you. Inclusive, candid, and relentlessly customer-obsessed. Please add a link in your résumé (GitHub repo, blog post, Kaggle entry, etc.) that shows something you taught yourself in the last six months and why it excited you.