Role & responsibilities:

1. GenAI Technical Lead:

Role Purpose:

Lead the design, development, and delivery of enterprise-grade Generative AI and Agentic AI solutions. Drive technical execution, mentor engineering teams, and ensure scalable, secure, and production-ready AI deployments.

Key Responsibilities:

- Lead end-to-end delivery of GenAI and Agentic AI solutions.

- Design and implement RAG, AI Agents, MCP, multi-agent orchestration, and LLM-based applications.

- Guide teams in prompt engineering, evaluation frameworks, guardrails, observability, and performance optimization.

- Translate business requirements into scalable AI solutions.

- Establish coding standards, architecture patterns, and engineering best practices.

- Conduct technical reviews and mentor GenAI engineers.

- Collaborate with architects, product owners, and business stakeholders.

- Drive production readiness, monitoring, security, and Responsible AI compliance.

Required Skills:

- Strong hands-on experience with Python, FastAPI, LangChain, LangGraph, Semantic Kernel, AutoGen, MCP.

- Experience with Azure AI Foundry, OpenAI, AWS Bedrock or similar platforms.

- Strong understanding of:

1. LLMs

2. RAG

3. Vector Databases

4. AI Agents

5. Prompt Engineering

6. LLM Evaluation

7. AI Observability

- Experience with CI/CD, MLOps, containerization, and cloud-native deployments.

- Strong stakeholder communication and leadership abilities.

Preferred candidate profile:

Experience:

- 612 years overall.

- 35 years in AI/GenAI.

Required Skills:

- Strong hands-on experience with Python, FastAPI, LangChain, LangGraph, Semantic Kernel, AutoGen, MCP.

- Experience with Azure AI Foundry, OpenAI, AWS Bedrock or similar platforms.

- Strong understanding of:

1. LLMs

2. RAG

3. Vector Databases

4. AI Agents

5. Prompt Engineering

6. LLM Evaluation

7. AI Observability

- Experience with CI/CD, MLOps, containerization, and cloud-native deployments.

- Strong stakeholder communication and leadership abilities.