Role Overview :

We are seeking an accomplished AI Technical Lead with 6+ years of experience in designing, developing, and deploying enterprise-grade AI solutions. The ideal candidate will lead initiatives around multi-agent systems, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), fine-tuning, context engineering, and AI-driven operations (AIOps).

Key Responsibilities :

- Design and implement multi-agent AI systems for enterprise workflows.

- Develop and optimize RAG pipelines for knowledge retrieval and contextual reasoning.

- Integrate MCP for tool and API interoperability across AI agents.

- Apply context engineering to improve agent reasoning and reliability.

- Fine-tune LLMs and transformer-based models for domain-specific tasks.

- Design and maintain knowledge graphs using Neo4J or similar graph databases.

- Lead development using Python (LangChain, HuggingFace, LangGraph, etc.).

- Ensure scalability, observability, and reliability of AI systems using AIOps practices.

Tech Stack & Requirements :

- 6+ years of experience in enterprise AI development.

- Expertise in multi-agent systems, RAG, MCP, and fine-tuning LLMs (HuggingFace, LoRA, PEFT).

- Proficiency in Python for AI pipelines and orchestration.

- Experience with data pipelines, ETL workflows, and knowledge graph creation (Neo4J).

- Exposure to ReactJS for UI development (nice to have).

- Experience with cloud-native AI deployments (Azure) and vector databases (PGVector, Pinecone, Milvus).

- Proven track record of leading technical teams and delivering enterprise-grade AI solutions.

Leadership & Collaboration :

- Mentor and guide engineering teams in AI best practices.

- Collaborate with product managers, data scientists, and stakeholders to align AI solutions with business goals.

- Drive innovation by evaluating emerging AI technologies and frameworks.