Lead AI/ML Engineer

• Design and build agentic AI systems with planning, tool calling, memory and multi-agent workflows using LangChain and LangGraph.
• Architect and optimise RAG pipelines: chunking, embeddings, vector search, re-ranking and evaluation.
• Build, train and deploy traditional ML and deep learning models with scikit-learn, PyTorch and TensorFlow.
• Write production-grade Python, expose models as APIs, and deploy on cloud with MLOps best practices.
• Lead and mentor ML/AI engineers, review code and designs, and partner with product and business teams.

Required skills

• 4–6 years of overall experience, including at least 1–2 years building LLM or GenAI applications.
• Expert-level Python (NumPy, Pandas, FastAPI, async).
• Hands-on experience with Agentic AI, LangChain, LangGraph and RAG.
• Practical experience with vector databases such as Pinecone, Weaviate, Qdrant, Milvus, Chroma or FAISS.
• Strong traditional ML skills with scikit-learn, PyTorch and TensorFlow, plus solid statistics and model evaluation.
• Working knowledge of Git, Docker and a cloud platform (AWS, Azure or GCP).
  • Bachelor's or master's degree in computer science, AI, Data Science or a related field.