Tech Lead, Generative AI Solutions

This is a unique opportunity to join Ingersoll Rand's new Generative AI Center of Excellence, where you’ll help shape the future of intelligent automation. We’re assembling a founding team to build the next generation of agentic AI systems—AI agents that can reason, plan, and act across complex operational domains. If you’re passionate about pushing the boundaries of what AI can do autonomously, this is your moment.

About the Role

As Tech Lead for Generative AI Solutions, you’ll take end-to-end ownership of building advanced AI agents from prototype to production. You will drive architecture and execution, lead multi-disciplinary teams, and manage relationships with key stakeholders to deliver high-impact GenAI solutions. This role blends deep technical leadership with hands-on execution, strategy, and team-building.

Core Responsibilities

• Agentic AI Architecture: Design and implement autonomous AI agents using frameworks such as LangGraph, Autogen, or CrewAI, integrating LLMs, memory, RAG, and tool-use capabilities.

• End-to-End Ownership: Lead the entire lifecycle—from ideation to production—of AI agent systems, including infrastructure design, deployment pipelines, scalability, monitoring, security, and governance.

• Project & Team Leadership: Own project planning and execution while directly managing engineering resources, timelines, and customer interactions. Act as the technical point person while coordinating across internal and external teams.

Qualifications

• Bachelor’s or Master’s in Computer Science, Artificial Intelligence, or a related technical field.

• 7+ years of software development experience, including significant time spent building AI/ML solutions.

• Strong Python skills and hands-on experience with modern AI/ML tools and cloud platforms.

• Proven experience leading complex projects involving multiple stakeholders and disciplines.

• Nice to have: - Experience with agentic AI frameworks like LangGraph, Autogen, CrewAI, MetaGPT. - Familiarity with vector databases (e.g. Pinecone, Weaviate, FAISS). - Knowledge of prompt orchestration, multi-agent coordination, and memory management in LLM pipelines.

Location: Hybrid (minutes from the train station)