Senior AI Engineer

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 teams.

We currently use LangChain's DeepAgent framework for our agent orchestration, but every layer of our AI stack is open to change. The right person for this role understands how agent systems work under the hood, not just one framework's abstractions.

What You'll Do:

• 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.
• Implementing robust tool-use patterns that connect agents to external systems (project management tools, CAD/PLM platforms, communication channels) via APIs and integrations.
• Designing and tuning prompts, chains, and retrieval strategies to maximize agent reliability, accuracy, and usefulness.
• 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 to end users.
• Collaborating with frontend engineers on the UX of AI-powered features and with backend engineers on data pipelines and API design.

Technical Requirements (Must Have):

• 5+ years of production software engineering experience, with 2+ years focused on bringing LLM-based applications or agent systems to market.
• Hands-on experience building and deploying agentic systems using frameworks such as LangChain/LangGraph, CrewAI, AutoGen, or custom orchestration.
• Strong Python proficiency in production environments.
• LLM fundamentals: prompt engineering, function/tool calling, retrieval-augmented generation (RAG), context window management, and token economics.
• Background job/async task pipeline experience (Celery, RQ, Temporal).
• Multi-agent systems with planning and delegation capabilities.
• Demonstrated proficiency using AI coding tools (Cursor, Copilot, Claude, etc.) to accelerate development.

Highly Valuable:

• Direct DeepAgent or LangGraph experience.
• LLM evaluation frameworks and prompt regression testing.
• Vector database familiarity (Pinecone, Weaviate, pgvector).
• Model serving, fine-tuning, or routing strategies.
• B2B SaaS / project management product background.
• Hardware development or engineering workflow knowledge.
• TypeScript/React for streaming agent UIs.

Compensation & Location: $143,000 - $215,000 base + performance bonus + long-term incentives (LTIP). Remote-first; preference for Boston, Seattle, Los Angeles, or Re:Build offices. Restricted to U.S. citizens or lawful permanent residents due to export control regulations.