Founding Engineer | $130K–$200K + Equity | AI × Supply Chain (Partner Role via CoffeeSpace) San Francisco (US)

About CoffeeSpace Partner Roles

This is a CoffeeSpace Partner Role — we work with select early-stage founders building ambitious, category-defining companies. We help them find their foundational hires through a mix of deep search, outbound, and semantic matching.

This particular role is with an early-stage AI startup in San Francisco building autonomous integration agents for the global supply chain.

The Company - In AI x Supply Chain

This company builds AI agents that automate B2B integrations across logistics, warehousing, and retail — transforming months of manual work into intelligent, autonomous workflows.

Today, supply chain integrations are slow and messy: analyst weeks, custom APIs, spreadsheet wrangling, brittle middleware, and long onboarding cycles.

Their LLM-powered integration agents replace all of that by:

* Learning and mapping systems autonomously

* Monitoring pipelines and fixing failures in real time

* Reducing engineering effort with every new deployment

The outcome: 10× faster, 10× cheaper integrations — without armies of consultants or custom one-off middleware.

The company has:

* Raised $1.6M from top-tier early-stage investors

* Multiple six-figure customer contracts already closed

* Production deployments live today, with strong demand from logistics tech vendors

If you want to build AI systems that automate real, messy, high-impact problems at the core of the global economy — this is that opportunity. A rare chance to join early, ship fast, and shape a new AI category.

The Founder

The founding team brings a mix of deep operational expertise and strong enterprise execution across logistics, supply chain, and integrations. Their experience includes:

* Amazon — operating at scale in complex supply chain and warehouse environments

* KPMG — delivering enterprise-grade audit, controls, and systems rigor

* Leading expansion at a fast-growing logistics startup, building warehouse networks from the ground up

* High-agency, high-velocity execution in unsexy, operationally intense industries ripe for AI transformation

The company sits at the intersection of domain depth × AI-native integration × rigorous execution.

The Role — Founding Engineer

You’ll be the first technical hire — building the core AI integration agents that automate the global supply chain. This role works directly with the founders and touches everything: frontend, backend, infra, and LLM-powered orchestration. You will architect, ship, and iterate fast alongside real customers.

You will

* Own the full product stack: backend (Node/TS), frontend (React), infra (AWS/Vercel), and internal tooling

* Build core agentic systems: autonomous system mapping, retries, queues, monitoring, exception pipelines

* Design and scale LLM pipelines + orchestration flows

* Work directly with founders on architecture, UX flows, and customer needs

* Dive into anything that moves the product forward — integrations, pipelines, infra, agents, or ops

* Own problems end-to-end without waiting for permission or strict specs

You’re right if you

* Work fast, take extreme ownership, and thrive in ambiguity

* Move comfortably between frontend, backend, infra, and LLM tooling

* Prefer shipping over debating; progress over perfection

* Have 3–8 years experience or exceptional 0→1 projects that prove you’re dangerous

* Communicate clearly and always close the loop

* Want to build in-person in San Francisco with a tight, high-velocity team

You’re wrong if you

* Need hand-holding or rigid structure to start

* Move slowly, over-intellectualize, or avoid ambiguity

* See yourself as “just backend,” “just frontend,” or “just infra”

* Want big-company pace, guardrails, or comfort

Compensation

Base Salary: $130,000–$200,000

Equity: 1.5%–3.0% equity

US Visa Support: O-1 Application Support

We target a competitive total compensation package (base + equity) aligned with early-stage founding roles. Equity packages offer significant long-term upside and will be discussed during the interview process.