Required Skills:
12+ years in full-stack or platform engineering, with recent hands-on GenAI work.
Strong skills in LLMs, RAG, embeddings, vector databases and multi-agent orchestration (LangChain, LangGraph, ADK or similar).
Python and/or TypeScript; REST APIs, event-driven integration, Docker and Kubernetes.
Cloud experience, preferably Azure (AWS or GCP is also fine).
Experience in customer-facing roles where you turned loosely defined business needs into shipped solutions.
Comfortable working in agile delivery, with fortnightly sprints and demos.
Summary
Build and ship GenAI solutions using LLMs, RAG, embeddings, vector databases and multi-agent orchestration with LangChain or similar. Requires 12+ years in full-stack or platform engineering with recent hands-on GenAI work, Python and/or TypeScript, REST APIs, Docker, Kubernetes and cloud experience.
Responsibilities
Turn loosely defined business needs into shipped solutions in customer-facing roles; work in agile delivery with fortnightly sprints and demos
Qualifications
12+ years in full-stack or platform engineering with recent hands-on GenAI work; Strong skills in LLMs, RAG, embeddings, vector databases and multi-agent orchestration; Python and/or TypeScript; REST APIs, event-driven integration, Docker and Kubernetes
Experience requirements
12+ years in full-stack or platform engineering, with recent hands-on GenAI work