AI Lead

IMR Soft LLC; New York (NY); On-site; USD 180,000 - 240,000; Full time

Job summary

IMR Soft LLC is seeking an AI Engagement Lead in NYC to drive GenAI projects for Fortune 500 customers. You will lead a cross-functional engineering team, design robust multi-agent architectures, and own the technical roadmap from concept to delivery.

The role requires deep GenAI expertise, strong Python/SQL skills, and hands-on experience with cloud platforms. You will mentor engineers and collaborate with business SMEs to deliver impactful AI products on-site in NYC.

Qualifications

• 12+ years of software engineering experience in building applications/systems.
• 2+ years hands-on experience with how LLMs work and multi-agent AI.
• Proficient in Python and SQL; experience with LangGraph.
• Architect GenAI apps using cloud services and frameworks.
• Experience with AI tools like Claude/Codex/Windsurf; AI observability with Langsmith/Langfuse.

Responsibilities

• Build the technical roadmap from business requirements and own delivery.
• Lead the engineering team toward the roadmap and ensure timely execution.
• Design robust multi-agent architectures with dynamic routing and control.
• Mentor engineers and promote best practices in ML and LLM development.
• Develop LLM-based solutions including training, fine-tuning, and deployment.
• Create agent evaluation pipelines and CI-integrated eval runs.
• Code in Python and SQL with reusable, scalable components.
• Deploy GenAI apps on Azure/GCP/AWS and optimize CI/CD.

Skills

12+ years exp

LLM multi-agent

Python

LangGraph

SQL

GenAI architectures

Cloud platforms

AI tools

Langsmith/Langfuse

Team leadership

Communication

Tools

Claude/Codex/Windsurf

Job description

AI Engagement Lead Location - NYC, NY Fulltime Permanent role Vetting Process - 3 Interviews including one in person interview at NYC, NY

About the role:

looking for people with GenAI experience to join us in solving business problems for our Fortune 500 customers. You will be a key member of the Intelligence delivery organization and part of a GenAI project. You will be required to lead a team of other engineers across different skill sets. In the past, the GenAI delivery organization has implemented industry leading multi-agent LLM systems and LLM deployments for major enterprises. Required skills:

• 12+ years of professional experience in software engineers and building applications/systems
• 2+ years of hands-on experience in how LLMs work & Generative AI (LLM) techniques particularly multi-agent systems.
• Expert proficiency in programming skills in Python, Langgraph and SQL is a must.
• Expert in architecting GenAI applications/systems using various frameworks & cloud services
• Expert proficiency in using AI tools like claude code, codex, cursor, windsurf and the likes.
• Expert proficiency in AI observability & evaluation tools like Langsmith, Langfuse or similar
• Good proficiency in using various cloud services from Azure, Google Cloud Platform, or AWS for building the GenAI applications
• Experience in driving the engineering team toward a technical roadmap.
• Excellent communication skills to effectively collaborate with business SMEs
  

Roles & Responsibilities:

• Solutioning & Lead
  • Build the technical roadmap given a business requirement and own the delivery of the same.
  • Lead the engineering team toward a technical roadmap and ensure timely execution of the roadmap to achieve customer satisfaction.
  • Design robust multi-agent architectures including supervisor-router patterns with dynamic sub-agent routing and stopping conditions
  • Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.
• Hands-on skills
  • Develop LLM-based solutions: Lead the design, training, fine-tuning, and deployment of large language models, leveraging techniques like retrieval-augmented generation (RAG) and multi-agent based architectures.
  • Build and maintain agent evaluation pipelines, including offline eval datasets, LLM-as-judge, and CI-integrated eval runs
  • Codebase ownership: Build & maintain high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.
  • Cloud integration: Deployment of GenAI applications on cloud platforms (Azure, Google Cloud Platform, or AWS), optimizing resource usage and ensuring robust CI/CD processes.
• Communication
  • Actively follows the frontier and has differentiated, up-to-date views on model releases, agentic architectures, evaluation methods, tool-use and computer-use patterns, multimodal capability, reasoning/test-time compute trends, and the serious open questions in the field.
  • Produce a structured, high-signal answer to an open-ended technical or strategic question while modulating depth for a non-engineering executive audience.
• Cross-functional collaboration: Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.