Technical Leadership

• Lead the architecture and development of GenAI solutions for enterprise use cases.
• Define AI application design standards, development guidelines, and best practices.
• Provide technical leadership and mentorship to AI/ML engineers and developers.
• Drive code reviews, solution reviews, and performance optimization.

GenAI Solution Development

• Design and implement applications using GPT, Azure OpenAI, Claude, Gemini, or open-source LLMs.
• Build Agentic AI workflows using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, and Semantic Kernel.
• Develop Retrieval-Augmented Generation (RAG) solutions using vector databases.
• Build conversational AI assistants, copilots, and enterprise knowledge solutions.

AI Engineering

• Develop prompt engineering strategies for business use cases.
• Fine-tune and optimize foundation models where applicable.
• Implement AI model evaluation, monitoring, and governance frameworks.
• Ensure responsible AI, compliance, and security standards.

Cloud & DevOps

• Deploy AI solutions on Azure, AWS, or GCP.
• Implement CI/CD pipelines for AI applications.
• Work with containerization technologies such as Docker and Kubernetes.
• Monitor performance, scalability, and operational efficiency.

Stakeholder Management

• Translate business requirements into AI-driven solutions.
• Collaborate with product, engineering, architecture, and business teams.
  • Present solution approaches and technical recommendations to leadership.