Product Engineer

**Seamflow** Product Engineer; £100K–£150K base per year + meaningful equity (~0.1%–1%); London (On-site)

**About Company** Seamflow builds AI-native software for the Testing, Inspection, and Certification (TIC) industry — a ~$300bn market that sits between manufacturers and regulators, verifying that products, processes, and systems meet safety, quality, and regulatory standards. It's a large, legacy industry built during the Industrial Revolution: still highly manual, resistant to change, and only now feeling real pressure to adopt AI. Seamflow builds a suite of tools that remove the manual bottlenecks in these workflows, and is one of the first companies doing it properly — rather than an off-the-shelf product, they build tools and customise them in granular detail to each customer's workflows.

Seamflow raised a 14x oversubscribed $4.5M seed round earlier this year from Initialized Capital and Northzone — the funds behind the founders of Coinbase, Reddit, Klarna, and Spotify — plus angels. They're already deployed inside most of the largest TIC players, seeing rapid revenue growth (demand outstripping supply), and plan to raise a Series A before the end of the year. The market is Euro-centric (hence the London HQ) but expanding into the US and China.

The team is ~11 people, scaling toward ~20. Engineering is world-class: a founding engineer from Fuse Energy (a ~$5bn company, where he was a first hire), people from X (working directly with Elon Musk), Amazon, Yandex, and JetBrains, plus AI researchers from MIPT, UCL, and Johns Hopkins. Commercially, the team includes the youngest-ever associate partner at McKinsey, managers from Bain, and Forbes 30u30 alumni. CTO Yusuf leads the technical vision; lead engineer Dimitri (ex-Fuse, first hire) sits beneath him, and the structure is deliberately flat — engineers sit together daily, argue out the best outcome, and every voice is heard.

**About the Role** The single Product Engineer seat. For someone who thinks in user workflows, not tickets — who wants to decide what should exist, build it end to end, and put it in users' hands. The differentiator (vs. the Forward Deployed Engineer) is product and UX ownership: turning complex, real-world TIC processes into clear, intuitive interfaces and being opinionated about what to build, skip, and ship. Same core stack (React/TypeScript + Python), same ship-from-day-one expectation.

**Responsibilities** - Own user-facing product end to end, from definition to deployment. - Turn complex real-world processes into clear, intuitive interfaces. - Build production-grade React/TypeScript frontend and Python backend. - Integrate LLMs, agents, and model-backed APIs into user workflows. - Be opinionated about what to build, what to skip, and when to ship. - Do what needs doing — from UX polish to debugging to the occasional customer call.

**Required Skills** A. Exceptional engineering pedigree (non-negotiable) — standout work at a top company, leading AI lab, elite trading firm, or fast-scaling startup. A famous logo isn't required, but it helps. B. Strong TypeScript and a modern frontend framework (React or equivalent), production-grade. C. Comfort building backend services in Python. D. Experience integrating AI systems into production products. E. Reasons about complex workflows, not just CRUD. F. Strong product and UX judgement — turns complexity into intuitive interfaces and decides what's worth building.

**Bonus Skills** - Full-stack flexibility (ideal), though exceptional strength in one area is fine. - Founder or ex-founder; early-stage, EF, YC, or Antler. - World-class CS/engineering education. - AI products shipped in production.

**Logistical Info** - Location: London, in-person at the Shoreditch HQ; outcome-focused with some flexibility. Open to relocation from anywhere. - Compensation: £100K–£150K base (set by experience, not role) + meaningful equity (~0.1%–1%). - Benefits/Other: Full visa sponsorship and relocation incl. flights; all meals in-office (breakfast, lunch, dinner); free gym membership.

**Ideal Background** - Strongest signal — high-ownership product startups (shipped real, user-facing products fast): Harvey, Happy Robot, Cursor, Ramp, Linear, Vercel, Lovable, n8n, Legora, Bending Spoons, Physical Intelligence, Anduril. - Also strong — big tech with genuine end-to-end product ownership: Google, Microsoft, Uber, ByteDance, Yandex, JetBrains, AWS, Datadog. - Also strong — seed-stage that exploded (Solve Intelligence, Fyxer) and acqui-hire alumni (Convergence Labs, Wiz, io, Hiro). - Key signal: owned a product surface end to end at production grade — not maintained a slice of a large system. Big tech straight out is fine if paired with founder mindset.

**Green Flags** - Founder mindset: high agency, high ownership, low ego. - Builds end to end at production grade and ships fast. - Thrives in unstructured, ambiguous problems — "builds order out of chaos." - Intensity — willing to work long hours, including nights/weekends when needed.

**Red Flags** - No founder mindset; only comfortable in a structured/corporate environment. - Multiple short stints (e.g. several ~6-month roles). - Contract roles rather than full-time. - Misleading or irrelevant job titles (e.g. "data trainer" at a big tech firm rather than a genuine SWE role). - Shiny logos without real depth or impact.

**Interview Process** Fast by design; fully remote — candidates may come on-site if they wish. 1. CV submission → reviewed almost immediately by Andrea Olivo (Founder's Associate). 2. Screening call (~30 min) with Andrea — motivations, early-stage startup appetite, willingness to work hard, past experience. 3. Technical conversation (~40 min) with a founding engineer — not an exam; an in-depth technical discussion. 4. Take-home task (~2 hours). 5. Final "vibe check" with both founders to sign off.