AI Engagement Lead (GenAI / LLM / Multi-Agent AI) {Local Candidate}

Job Title: AI Engagement Lead (GenAI / LLM / Multi-Agent AI)

Location: New York City, NY (3 days Onsite, 2days Remote)
Interview Process: 3 Rounds (Final Round In-Person in NYC)
Experience: 12+ Years

Job Description

We are looking for an experienced AI Engagement Lead to lead the design, architecture, and delivery of enterprise Generative AI solutions for Fortune 500 clients. This role is ideal for a hands-on technical leader with deep expertise in LLMs, Multi-Agent AI Systems, LangGraph, Python, and Cloud Platforms.

You will work closely with business stakeholders, architects, product owners, and engineering teams to build scalable AI applications using modern GenAI frameworks and best practices.

Required Skills

• 12+ years of software engineering experience
• 2+ years of hands-on experience with Generative AI and Large Language Models (LLMs)
• Strong expertise in Multi-Agent AI architectures
• Expert-level Python development
• Strong SQL skills
• Hands-on experience with LangGraph (LangChain is also valuable)
• Experience designing enterprise GenAI applications
• Experience implementing RAG (Retrieval-Augmented Generation)
• AI evaluation and observability using:
• LangSmith
• LangFuse
• Similar AI evaluation tools
• Experience with AI coding tools:
• Claude Code
• Cursor
• Windsurf
• Codex
• Experience deploying GenAI applications on AWS, Azure, or Google Cloud Platform
• CI/CD knowledge
• Strong communication and leadership skills
• Experience mentoring engineering teams

Responsibilities

• Lead architecture and delivery of enterprise GenAI applications
• Design and implement Multi-Agent AI systems
• Build scalable RAG pipelines
• Develop AI solutions using Python, LangGraph, SQL, and cloud platforms
• Create AI evaluation pipelines using LangSmith/LangFuse
• Lead technical roadmap and engineering execution
• Collaborate with Fortune 500 business stakeholders
• Mentor engineers and establish AI best practices
• Deploy production-grade AI systems using cloud infrastructure
• Stay current with advancements in LLMs, reasoning models, AI agents, multimodal AI, and AI evaluation techniques