Job Description :

We are looking for an AI Technical Lead with strong hands-on experience in Generative AI, LLMs, RAG, Multi-Agent Systems, MCP, and AI architecture. The role involves designing and delivering enterprise AI solutions, building scalable AI platforms and data pipelines, and providing technical leadership across AI engineering teams.

Key Responsibilities :

- Design and lead enterprise AI solutions using LLMs, RAG, Multi-Agent Systems, MCP, and LLM fine-tuning.

- Define scalable AI architectures covering models, agents, orchestration, knowledge, data, APIs, and deployment infrastructure.

- Design and implement RAG pipelines, including document ingestion, chunking, embeddings, retrieval, reranking, context management, and evaluation.

- Develop multi-agent systems and agentic workflows for complex enterprise use cases.

- Design and implement MCP-based integrations to connect AI agents with enterprise tools, systems, and data sources.

- Apply context engineering and prompt engineering techniques to improve model accuracy, reliability, and task performance.

- Work with LLM fine-tuning, model adaptation, evaluation, and optimization where required.

- Build knowledge-driven AI solutions using knowledge graphs, vector databases, and enterprise data platforms.

- Develop scalable AI/data pipelines using Python and modern AI/ML frameworks.

- Lead AI solution development from PoC through production deployment, including testing, evaluation, monitoring, and optimization.

- Define standards for AI application architecture, security, scalability, observability, governance, and responsible AI.

- Collaborate with Product, Data, Engineering, Cloud, and Business teams to translate enterprise requirements into AI solutions.

- Evaluate emerging AI technologies, models, frameworks, and tools and recommend their application to business use cases.

- Provide technical leadership, conduct architecture and code reviews, and mentor AI engineers.

- Support technical solutioning, client discussions, estimation, and enterprise AI strategy where required.

Required Skills:

- 6 - 11 years of experience in AI/ML, Software Engineering, Data Science, or related technical domains.

- Strong hands-on experience with Generative AI and LLM-based applications.

- Proven experience building RAG and Multi-Agent/Agentic AI systems.

- Strong understanding of MCP (Model Context Protocol) and tool-based AI integrations.

- Experience with LLM fine-tuning, model adaptation, evaluation, and optimization.

- Strong understanding of context engineering, prompt engineering, embeddings, vector search, and retrieval techniques.

- Strong proficiency in Python.

- Experience with AI/LLM frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or equivalent.

- Experience with vector databases and knowledge systems; exposure to knowledge graphs is preferred.

- Experience designing and deploying scalable AI solutions on AWS, Azure, GCP, or equivalent cloud platforms.

- Understanding of AI evaluation, observability, security, governance, and responsible AI practices.

- Strong system-design, architecture, problem-solving, technical leadership, and stakeholder-management skills.

- Experience taking enterprise AI solutions from PoC to production is strongly preferred.