Skip to content
NEXTMOVEFDE careers · United States

Senior AI Engineer

Technologies

LangChain · LangGraph · DeepAgent · CrewAI · AutoGen · Python · LLM · RAG · Celery · Temporal

About Re:Build Manufacturing

Holding company assembling US-based engineering and manufacturing businesses to revitalize American industrial production across aerospace, defense, biotech, and energy.

Growth

Job description

The full responsibilities and requirements are on the employer’s site.

Read the job description
Source and classification

Internal deployment & tooling · Evidence for this classification:

communities where we operate. (link to The Re:Build Way principles) The Opportunity If you've worked alongside hardware teams, you know the damage that results from a missed change request or critical context that was never relayed to the right person. Reflow exists to close that gap. We're building the first AI-powered platform built for hardware product development, one that listens across the tools teams already use, maintains a structured picture of every program, and proactively coordinates across disciplines when things inevitably change. This is an early role for a hands-on AI engineer to design and build the agents at the core of our platform, backed by a parent company with deep roots in engineering and manufacturing. You'll own the AI systems that set our product apart: agents that understand hardware workflows, anticipate problems, and take action on behalf of engineering
More from the job description

About Re:Build At Re:Build, our mission is to ensure the next generation of important products are made, at scale, in America. We are laying the foundation for a better future for our customers, employees, and communities by revitalizing America's manufacturing base and creating meaningful jobs across the country, including in historically deindustrialized regions. We operate an advanced, end-to-end manufacturing platform that partners with industrial companies and innovators to take products from first concept to full-scale production in critical verticals including aerospace and defense, electrification, medical, energy and environment, and robotics and automation. The way we operate is as important as the work we do. It's guided by The Re:Build Way, 16 principles that shape how we collaborate with each other, partner with our customers and vendors, and contribute to the communities where we operate. (link to The Re:Build Way principles) The Opportunity If you've worked alongside hardware teams, you know the damage that results from a missed change request or critical context that was never relayed to the right person. Reflow exists to close that gap. We're building the first AI-powered platform built for hardware product development, one that listens across the tools teams already use, maintains a structured picture of every program, and proactively coordinates across d [... source excerpt omitted ...] s an early role for a hands-on AI engineer to design and build the agents at the core of our platform, backed by a parent company with deep roots in engineering and manufacturing. You'll own the AI systems that set our product apart: agents that understand hardware workflows, anticipate problems, and take action on behalf of engineering teams. Who We're Looking For We're looking for an AI engineer who works equally well in applied research and production software. You've shipped LLM-powered agent systems to real users, you have strong intuitions about prompt engineering, tool use, and orchestration patterns, and you keep up with a field that changes fast. You're comfortable e [... source excerpt omitted ...] roduct to build, optimize, and operate the AI agents that give users proactive coordination, risk surfacing, status summaries, and AI-generated deliverables. The role is hands-on. You'll write code daily while contributing to AI architecture decisions and helping define how we evaluate and evolve our agent capabilities over time. What You'll Do Your day-to-day responsibilities will include: Designing, building, and iterating on LLM-powered agents that coordinate across engineering disciplines, surface project risks, and generate structured deliverables (proposals, SOWs, status reports) Owning the agent orchestration layer (currently LangChain DeepAgent) and continuously eva

How jobs are selected

Employer postings · Data from · Sources