Staff Software Engineer - AI Apps

Staff Software Engineer, AI Apps — AI-native productivity, stealth

Fully remote, UK-based candidates preferred.

Do you have the following skills, experience and drive to succeed in this role Find out below.

TL;DR

• Founding-team Staff Engineer role at a well-funded stealth AI company
• Product: AI-native productivity — starting with email, expanding into notes, tasks, calendar
• Own the full engineering layer: backend systems, APIs, and client applications
• The hard part isn't the AI — it's making it reliable at scale
• US$100M initial funding, internally backed, no VC pressure
• Cash + meaningful founding-team equity
• Fully remote

The play

Email, calendar, notes, tasks. The tools 5 billion people run their lives on. None of them are AI-native. Every attempt so far has been a bolt-on — a copilot button in the corner, a summary at the top of the thread. This company is building the opposite: a proactive layer underneath that reads context, runs long workflows, completes real tasks, and asks before it acts. First product is an AI-native email app. Cut the four hours a day the average knowledge worker spends in their inbox down to thirty minutes. Email first. Productivity suite next.

The role, first 12 months

Own the application engineering strategy and execution across backend, mobile, and desktop. Design systems that can handle the real complexity of AI-powered products — state management, orchestration, tool use, retries, fallbacks, and graceful failure. Build the APIs and abstractions that connect AI capability to actual product experiences. Lead a small team of senior engineers through design reviews, code reviews, and hands-on mentorship. Make the hard trade-offs across latency, reliability, cost, security, and UX — and ship.

The bar

Read this before you DM.

• Significant experience leading application or product engineering for complex, production systems
• Strong backend engineering fundamentals — you've built and shipped systems people actually use
• Experience building the systems around AI — orchestration, tool use, state, retries, and failure handling — not just calling an API and rendering the output
• Comfortable across backend and client platforms, with deep expertise in at least one
• Strong technical judgement — you make good calls with incomplete information and own the outcome
• Zero-to-one experience — you know what pre-launch engineering actually feels like

Who this isn't for

Engineers who want to manage tickets and attend standups. People whose AI experience begins and ends with wrapping a ChatGPT endpoint. If your production systems don't exist outside of a demo, this isn't the role. xwzovoh

The rest

Everything else — who they are, who's behind it, comp and equity detail — is a call.

DM me if this sounds like the room you want to be building in.