SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Re:Build Manufacturing is revitalizing America's manufacturing base through an advanced, end-to-end manufacturing platform serving aerospace and defense, electrification, medical, energy, and robotics sectors. The company is building Reflow, an AI-powered platform designed specifically for hardware product development that listens across existing tools, maintains structured program visibility, and proactively coordinates across disciplines when changes occur.
You'll join as a hands-on Senior AI Engineer to design and build the LLM-powered agents at the core of Reflow's platform. This is an early-stage role with significant technical ownership and architectural influence. Your primary focus will be developing agent systems that understand hardware workflows, anticipate problems, and take coordinated action on behalf of engineering teams.
Key responsibilities 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 evaluating whether to extend, replace, or supplement it as new frameworks emerge
- Implementing robust tool-use patterns connecting agents to external systems via APIs (project management, CAD/PLM platforms, communication channels)
- Designing and tuning prompts, chains, and retrieval strategies to maximize agent reliability and usefulness across diverse hardware contexts
- Building evaluation and observability infrastructure for agent performance, including tracing, cost tracking, latency monitoring, and automated quality benchmarks
- Developing streaming agent interfaces that surface real-time progress, reasoning transparency, and proactive alerts
- Staying current with rapid advances in LLMs and agent frameworks, translating awareness into actionable recommendations
- Collaborating with frontend and backend engineers on AI feature UX and data pipelines
- Contributing to AI architecture decisions and engineering best practices
Required qualifications: 5+ years production software engineering experience with 2+ years bringing LLM-based applications or agent systems to market. Demonstrated proficiency with AI coding tools (Cursor, Copilot, Claude). Hands-on experience building and deploying agentic systems using frameworks like LangChain/LangGraph, CrewAI, or AutoGen. Strong understanding of LLM fundamentals including prompt engineering, function/tool calling, RAG, and context management. Experience with production observability and evaluation frameworks for AI systems.
