Gen AI & Agentic Sys Engineer

Responsibilities:

• Design and build Retrieval-Augmented Generation (RAG) pipelines for 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.

Requirements:

• 2-3 years of hands-on experience building and shipping software, with meaningful exposure to LLM / GenAI systems.
• Comfort working independently on ambiguous problems and turning prototypes into production-grade services.
• A strong grasp of software fundamentals: clean code, version control, testing, and reproducible deployments.
• Curiosity about the rapidly evolving AI ecosystem and a habit of evaluating new tools critically.
• Good communication skills and the ability to collaborate with non- technical stakeholders.
• Qualification: Bachelor's degree in Computer Science, Engineering, or a related field or equivalent practical experience.

Must-Have Skills:

• You should have strong, demonstrable experience with: Python, LangChain / LangGraph, RAG architectures, Vector databases Pinecone, Weaviate, Chroma, FAISS, or Qdrant, LLM APIs OpenAI, Anthropic, and/or Gemini, Prompt engineering, Embeddings and semantic search, AI agents and tool calling, FastAPI / Flask and REST API design, PostgreSQL / MongoDB, Docker, Git and CI/CD workflows.

Bonus Points If You've Worked With:

• LlamaIndex, CrewAI / AutoGen and multi-agent workflows, Fine-tuning open-source LLMs, Inference optimisation vLLM, Ollama, Cloud platforms AWS or GCP, Real-time streaming systems, OCR / document intelligence, Evaluation frameworks Ragas, DeepEval, LangSmith, Redis.

Skills

LangChain, LangGraph, Python, RAG, Retrieval-Augmented Generation