GenAI & Agentic System Engineer

What You''ll Do

• Design and build Retrieval-Augmented Generation (RAG) pipelines
• chunking, embeddings, semantic search, and retrieval tuning for accuracy
• and grounding.
• Develop AI agents and multi-step workflows using LangChain / LangGraph,
• including tool calling and orchestration across multiple steps.
• Build and maintain backend services and REST APIs (FastAPI / Flask) that
• expose AI capabilities to internal and member-facing applications.
• Integrate and optimise usage of LLM providers (OpenAI, Anthropic, Gemini),
• balancing quality, latency, and cost.
• Work with vector databases (Pinecone, Weaviate, Chroma, FAISS, or Qdrant)
• and relational/document stores (PostgreSQL / MongoDB) for storage and
• retrieval.
• Apply strong prompt engineering practices and iterate based on evaluation
• results.
• Containerise and deploy services with Docker, and contribute to Git-based
• CI/CD workflows.
• Set up evaluation and quality checks for AI outputs, and continuously
• improve reliability and accuracy.