• Design, develop, and deploy LLM applications, RAG systems, multi-agent workflows, and scientific AI solutions, and build scalable AI services supporting engineering co-pilots and knowledge assistants.

• Fine-tune and optimize foundation models, and build embedding pipelines, vector search systems, and agent orchestration frameworks.

• Evaluate model performance, hallucination rates, and business impact.

• Develop production quality systems using Python, FastAPI, LangGraph, LangChain, and Semantic Kernel, and build APIs and reusable AI services.

• Integrate AI solutions with Databricks, Azure AI Foundry, and AWS.

• Mentor junior engineers, design architectures, establish engineering best practices, and collaborate with product and business stakeholders.

• Independently deliver solutions alongside guiding team members.

Functional Knowledge

• Demonstrates depth and/or breadth of expertise in Generative AI with strong fundamentals in software engineering

Business Expertise

• Interprets internal/external business challenges and recommends best practices to improve products, processes or services

Problem Solving

• Leads to solve complex problems; uses sophisticated analytical thought to exercise judgment and identify innovative solutions

Interpersonal Skills

• Communicates advanced concepts and negotiates with others to adopt a different point of view

• Proliferation of knowledge, learnings and best practices across the team

Required Qualifications

• BS/MS in Computer Science, Data Science, or Software Engineering

• 5 to 8 years of Software Engineering / Machine Learning experience

• End-to-end understanding of development from technical architecture to production deployment

• Strong understanding of system design and SDLC in Enterprise

• 2+ years of  hands-on Generative AI experience

• Expertise in Python, LangGraph, Transformers, LLMs, and Integrations

  • Experience building production grade, scalable AI systems