Architect and implement Generative AI solutions using Python and modern AI frameworks.
Lead development efforts involving LangChain, LangGraph, LangSmith, and agentic AI workflows.
Integrate and optimize AI models on Azure OpenAI, AWS Bedrock, and other cloud platforms.
Design and manage multi-agent systems leveraging MCP (Model Context Protocol) for orchestration.
Collaborate with cross-functional teams to define technical strategy, best practices, and coding standards.
Ensure scalability, security, and compliance in AI deployments across enterprise environments.
Mentor and guide engineers on advanced AI concepts, coding practices, and system design.
Stay ahead of trends in Generative AI, LLMs, and agent-based architectures to drive innovation.

Bachelor’s/Master’s degree in Computer Science, Engineering, or related field
10+ years of experience in software development, with at least 4+ years in AI/ML systems
Strong proficiency in Python and experience with AI libraries (e.g., PyTorch, TensorFlow)
Hands-on expertise with LangChain, LangGraph, LangSmith, and related orchestration tools
Proven experience with Azure OpenAI, AWS Bedrock, and cloud-native AI deployments
Knowledge of MCP and multi-agent architectures for AI workflows
Familiarity with CI/CD pipelines, containerization (Docker/Kubernetes), and microservices
Excellent problem-solving, communication, and leadership skills.

Principal Lead AI Engineering

Key skills