Senior AI Engineer

About the Role

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 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 partnering 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.

Reflow, our AI-powered platform, exists to close the gap caused by missed change requests or critical context not relayed to the right person in hardware product development. As an early AI engineer, you will 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.

Responsibilities

• Design, build, and iterate on LLM-powered agents that coordinate across engineering disciplines, surface project risks, and generate structured deliverables (proposals, SOWs, status reports).
• Own the agent orchestration layer (currently LangChain DeepAgent) and continuously evaluate whether to extend, replace, or supplement it as new frameworks and patterns emerge.
• Implement robust tool-use patterns that connect agents to external systems (project management tools, CAD/PLM platforms, communication channels) via APIs and integrations.
• Design and tune prompts, chains, and retrieval strategies to maximize agent reliability, accuracy, and usefulness across diverse hardware project contexts.
• Build evaluation and observability infrastructure for agent performance, including tracing, cost tracking, latency monitoring, and automated quality benchmarks.
• Develop streaming agent interfaces that surface real-time progress, reasoning transparency, and proactive alerts to end users.
• Stay current with rapid advances in LLMs, agent frameworks, and related tooling, and translate that awareness into actionable recommendations for the team.
• Collaborate with frontend engineers on the UX of AI-powered features and with backend engineers on data pipelines and API design.
• Contribute to AI architecture decisions, code reviews, and engineering best practices.

Requirements

• 5+ years of production software engineering experience, with 2+ years focused on bringing LLM-based applications or agent systems to market.
• Demonstrated proficiency using AI coding tools (Cursor, Copilot, Claude, etc.) to accelerate development.
• Hands-on experience building and deploying agentic systems using frameworks such as LangChain/LangGraph, CrewAI, AutoGen, or custom orchestration.
• Strong understanding of LLM fundamentals: prompt engineering, function/tool calling, retrieval-augmented generation (RAG), context window management, and token economics.
• Proficiency with Python in production environments.
• Experience integrating LLM-powered features with external APIs, databases, and third-party tools.
• Experience designing and operating background job / async task pipelines (Celery, RQ, Temporal, or similar) for long-running agent runs and reliable retries.
• Experience building multi-agent systems with planning, delegation, and inter-agent communication patterns.
• Demonstrated ability to evaluate and adopt new AI tools and frameworks quickly, with a track record of staying ahead of a fast-moving field.
• Strong software engineering fundamentals: clean architecture, testing, version control, and code review practices.
• Ability to balance rapid experimentation with production-grade reliability.

Qualifications

• Direct experience with LangChain's DeepAgent or LangGraph for multi-step agent orchestration.
• Background in evaluation frameworks for LLM outputs (automated scoring, human-in-the-loop evaluation, regression testing for prompts).
• Familiarity with vector databases and embedding pipelines (Pinecone, Weaviate, pgvector, or similar).
• Experience with model serving infrastructure, fine-tuning workflows, or model selection/routing strategies.
• Understanding of authentication/authorization patterns (OIDC, JWT) and secure handling of user data in LLM contexts.
• Background in B2B SaaS platforms, project management tools, or technical collaboration products.
• Familiarity with hardware development, engineering workflows, or project management concepts (phases, gates, dependencies, requirements traceability).
• TypeScript / React fluency, enough to pair with frontend engineers on streaming agent UIs and reasoning-transparency surfaces.

Benefits

• Full health, dental, and vision coverage.
• Bonus program.
• Generous 401K.
• Paid time off.
• Annual learning stipend.
• Participation in Re:Build's LTIP equity program and opportunity for founder equity in potential spin-out.

Pay

The base salary range for this position is $143,666.72 - $215,500.08 per year. Actual compensation will be determined based on relevant experience, skills, qualifications, internal equity, and geographic location. This role may also be eligible for annual incentive compensation and/or long-term incentives, subject to Company plans.

Schedule

This is a remote-first role, with preference for candidates in Boston, Seattle, Los Angeles, or other cities with Re:Build offices.

Please note this role is restricted to US citizens or lawful permanent residents only due to exposure to export controlled information.