Type: Full-time | On-site | San Francisco, CA Compensation: $165K–$190K + meaningful early-stage equity Visa sponsorship: Open to transfers (OPT, H1B) and new sponsorships (new H1B, TN)

Our client is a well-funded, seed-stage startup using AI to modernize a large, traditionally underserved corner of the global supply chain. Their platform is already live in production with significant industry customers and is growing quickly through word-of-mouth. You'd join as one of the first engineers, working directly with the founding team.

Stage: seed-stage · Small founding team · Industry: AI, B2B, Data, Enterprise, Logistics, Software

• Big market, real traction: live in production with major customers in a huge, traditional industry, and growing quickly through word-of-mouth.
• Well-backed early-stage team: recently closed a seed round led by respected investors.
• Strong founding team: a technically deep founder from the AI world alongside a co-founder with extensive domain expertise in the industry.
• True founding-engineer ownership: own your product streams and customer relationships from week one, with a clear path to leading your own engineering team as the company grows.

Join as one of the first engineers at a fast-growing startup using AI to modernize a large, traditional supply-chain industry. You'll work directly with the CTO, own entire product streams from day one, and build the data infrastructure that powers the product for major industry customers.

What you'll be doing

• Building and hardening robust data pipelines that process live production data from legacy enterprise systems (some decades old) for large industrial customers
• Owning a product stream end-to-end — from customer conversations to shipped features — early in your tenure
• Deploying and customizing data-ingestion tools across customers with different file formats, ERPs, and integration requirements
• Communicating directly with non-technical customers to learn the industry and gather requirements
• Contributing to AI agent development, including voice AI applications and LLM-powered data ingestion

Tech stack: Python, TypeScript, SQL, .NET, AI Agent SDKs, Claude Code, Cursor, Codex

• 1–5 years building full-stack or backend systems, with strong Python and TypeScript
• A track record of shipping backend systems to production (SaaS, services, or data infrastructure)
• Hands-on experience building or maintaining data pipelines at scale
• Evidence of a steep growth curve — early promotions, side projects, or open-source work you can point to
• A clear, concise communicator who can explain technical concepts to non-technical people — this is a genuinely customer-facing engineering role
• A degree in a quantitative or problem-solving field (CS, physics, math, engineering), or equivalent hands-on experience backed by a strong record of shipping

• Experience at a high-bar startup or fast-moving company
• Built integrations with legacy or enterprise systems (ERP, EDI)
• An AI-native developer who actively uses modern AI coding tools (Cursor, Claude Code, Codex) and has real opinions on them
• Non-traditional or self-taught backgrounds are welcome where backed by real, shipped work
• Evidence of high-level competitiveness outside engineering (e.g. competitive athletics, martial arts, music at the highest grades)

• Salary: $165K – $190K
• Equity: Meaningful early-stage equity
• On-site policy: 5 days/week in-office, San Francisco
• Visa sponsorship: Open to transfers (OPT, H1B) and new sponsorships (new H1B, TN)
• Employment type: Full-time
• Location: San Francisco, CA

Stage 1 — Initial Screen with the CTO (20 min) A culture-fit and vibe-check call with the CTO/co-founder. Not a technical assessment — the focus is on team fit, clear communication, and personality.

Stage 2 — Technical Interview: GitHub Project Deep Dive with the CTO (60 min) Select a GitHub project and send it in advance. The interview opens with a 20-minute demo/presentation of the project, followed by 40 minutes of deep technical discussion of what you built, the trade-offs you made, and your personal contributions.

Stage 3 — Technical Assessment: Debugging AI-Written Code (40 min) A live 40-minute assessment on an AI-generated codebase with intentional bugs. You'll read, identify, and fix the bugs, and are encouraged to use AI coding tools. This evaluates how well you understand and debug AI-written code and how systematically you use AI tooling.

Stage 4 — Paid Work Trial (1 day) A one-day paid trial working alongside the team on real tasks — the final evaluation of engineering ability, collaboration, speed, and communication. Ideally in-person in San Francisco; remote arrangements possible depending on circumstances.

Stage 5 — Offer Extended

Stage 6 — Candidate Hired