About the Role:

We are looking for a GenAI / Agentic AI Lead / Architect to design, build, and scale enterprise-grade AI solutions powered by LLMs, Agentic AI, RAG, and modern AI frameworks.

The ideal candidate will have strong hands-on expertise in designing LLM-powered applications and multi-agent systems, along with the ability to take AI solutions from architecture and POC through production deployment and optimization.

This role requires a combination of technical leadership, AI architecture, hands-on development, system design, and mentoring.

Key Responsibilities:

- Design and architect GenAI and Agentic AI solutions for enterprise use cases.

- Build production-grade LLM applications, AI agents, multi-agent workflows, and intelligent automation systems.

- Design agent architectures involving planning, reasoning, tool calling, memory, orchestration, and autonomous task execution.

- Develop RAG pipelines including document ingestion, chunking, embeddings, retrieval, reranking, context management, and response generation.

- Work with LLMs from OpenAI, Anthropic, Azure OpenAI, Gemini, Llama, Mistral or equivalent platforms.

- Build and orchestrate AI agents using frameworks such as LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI or equivalent.

- Design integrations between LLMs, enterprise applications, APIs, databases, search engines, and external tools.

- Develop scalable Python-based AI services and APIs using FastAPI or equivalent frameworks.

- Design solutions for LLM evaluation, observability, guardrails, reliability, security, and cost optimization.

- Lead the transition of GenAI / Agentic AI solutions from POC to production.

- Define technical architecture, design patterns, coding standards, and best practices for GenAI applications.

- Evaluate new LLMs, agent frameworks, vector databases, AI platforms, and emerging GenAI technologies.

- Mentor AI / ML engineers and provide technical leadership across AI initiatives.

- Collaborate with product, engineering, data, security, and business teams to translate requirements into scalable AI solutions.

Mandatory Skills:

- Strong hands-on experience with Generative AI / LLMs.

- Strong experience in Agentic AI / AI Agents / Multi-Agent Systems.

- Strong Python programming skills.

- Hands-on experience with LangChain and / or LangGraph.

- Strong understanding of LLM architecture and application development.

- Strong experience building RAG-based applications.

- Experience with LLM APIs and model integration such as OpenAI, Azure OpenAI, Anthropic, Gemini, Llama, or Mistral.

- Experience with prompt engineering, tool / function calling, structured outputs, memory and context management.

- Experience designing and developing REST APIs / FastAPI.

- Good understanding of vector databases and semantic search.

- Experience taking AI solutions from development / POC to production.

- Strong understanding of AI system architecture, scalability, security and performance.

Agentic AI / Framework Expertise:

Strong hands-on experience with one or more of:

1. LangGraph

2. LangChain

3. LlamaIndex

4. AutoGen

5. CrewAI

6. Semantic Kernel