Software Engineer, Agentic Workflows

Rebar•New York City, NY

22h•Onsite

About The Position

Rebar is building the AI operating system for commercial HVAC, Electrical, and Plumbing. Over the past year our quoting platform has processed tens of thousands of projects across North America and we’re continuing that growth. Our customers include many of the top firms in the industry. Some of these companies are running billion dollar construction projects on workflows that still look like it's 1985. Construction is 10% of GDP and still massively underserved by software. We are changing that. We recently raised a $14M Series A from leading construction tech investors and are entering our next phase of growth. We are building a set of AI native products that will define how this industry operates. About the Engineering Org We're in the age of ai and the role of the engineer is rapidly changing. We're aware. We're being very intentional of ensuring we adapt with it. We are fostering an engineering culture of growth and development. We strongly emphasize care of craft and winning together. About the Role We're looking for a talented Software Engineer to build the platform and context layer for our Rebar Agent. This role will include utilizing the frameworks, services, and tooling that make agentic workflows reliable, scalable, and genuinely useful in production. This is a hands-on role with broad impact: you're about to build the backbone for an agent, understand a user’s current context, access the right data safely, and take actions with strong guardrails. You'll own this from zero: context modeling, retrieval and indexing, orchestration and tool-calling architecture, evals/observability, and cost + latency. This is a high-leverage product surface for the company, and it's a full-stack role - you'll be writing TypeScript on the UI in the morning and Python on the orchestration layer in the afternoon. You'll join a small, highly capable engineering team building the future of cutting edge construction tech.

Requirements

6+ years of industry software development experience
Full-stack chops comfortability
Deep familiarity with LLM tool use / function calling
Evals and iteration, not just ripping vibes
Comfort with ambiguity
Product taste, especially for trust

Nice To Haves

Built LLM eval harnesses with acceptance / reject / edit-then-accept tracking, or similar trust metrics
RAG over large document corpora (construction plansets can be 300+ pages and very dense)
Experience with agent frameworks
Shipped LLM features where token cost or p95 latency was a hard constraint
Experience with streaming UIs , generative UI patterns, or Cursor/PostHog-style chat interfaces
Experience with Next.js in production
Familiarity with real-time features
Interest in construction, manufacturing, or domain-specific software

Responsibilities

Design and maintain backend services and orchestration systems that power agentic workflows and tool execution.
Build the context layer - indexing, retrieval, and structured representations so the agent can ground itself in the right information without re-reading everything.
Integrate LLMs into product surfaces safely - permissions, guardrails, and acceptance-gated write actions
Stand up evals + observability - measure quality (accept/reject/edit-then-accept), reliability, and regressions; iterate quickly.
Collaborate cross-functionally with ML and product to bring new capabilities into production and improve developer/customer experience.