Generative AI Engineer

About the Role

We are seeking an AI Engineering Lead with deep technical expertise and a builder’s mindset. This role is ideal for someone who thrives at the intersection of LLM innovation, system design, and engineering rigor . You will be responsible for designing and deploying advanced AI applications at scale — from autonomous agents to retrieval-augmented generation (RAG) pipelines — powering intelligence solutions that impact real-world decisions in regulated industries.

This isn’t just a data science role — it’s a hands-on engineering position demanding architectural foresight, curiosity, and a constant pulse on evolving AI capabilities.

Key Responsibilities

• Design and build AI-powered platforms , including multi-agent orchestration (CrewAI, AutoGen, LangGraph) and RAG pipelines (dense / sparse / hybrid search strategies).
• Operationalize AI across use cases like data harvesting, compliance validation, summarization, and knowledge retrieval .
• Lead end-to-end implementation of LLM systems using open-source stacks — LangChain, Haystack, HuggingFace, etc.
• Develop web-integrated AI applications , collaborating with front-end and backend teams (React, FastAPI, etc.).
• Drive quality, scalability, and reliability in all AI product engineering efforts, ensuring robust deployment and monitoring.
• Own embedding lifecycle, prompt strategy, agent memory , and dynamic tool invocation techniques.
• Collaborate cross-functionally across product, infra, data, and legal teams to ensure business-aligned engineering.
• Stay ahead of the curve — proactively track AI tool evolution, contribute PoCs, and guide architectural decision-making.

Required Qualifications

Working knowledge of cloud environments (AWS / GCP) , containerization, CI / CD, and model monitoring.