Engineering Manager, AI Product and Platform

𝗥𝗲𝗺𝗼𝘁𝗲 (𝗳𝗼𝗿 𝗨𝗔𝗘 𝗖𝗼𝗺𝗽𝗮𝗻𝘆) · 𝗔𝗜 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 & 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺 · 𝗘𝗠, 𝗟𝟱 · 𝗠𝗝𝗗𝟬𝟴.𝟬.𝟭 Hands-on engineering manager who 𝗹𝗲𝗮𝗱𝘀 𝗮𝗻𝗱 𝘀𝘁𝗶𝗹𝗹 𝗯𝘂𝗶𝗹𝗱𝘀 the team that makes the application in which 𝗽𝗲𝗼𝗽𝗹𝗲 𝘄𝗮𝘁𝗰𝗵, 𝘁𝗲𝗮𝗰𝗵, 𝗰𝗼𝗿𝗿𝗲𝗰𝘁 𝗮𝗻𝗱 𝗮𝗽𝗽𝗿𝗼𝘃𝗲 𝘄𝗵𝗮𝘁 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀 𝗱𝗼, and the platform it runs on. Greenfield. THE TECHNICAL CHALLENGE We build agents on open-weight LLMs that operate web applications through the browser. People who are not developers supervise these agents from one application. This team builds that application and the platform beneath it. What the agents produce becomes stable interfaces that other systems rely on, with a record of what was done. The manager sets the technical direction of both, decides what is released and hires the team. The manager agrees with the research team what each side can rely on. Work is accepted as working software, shown to the people who use it. This role leads the team that builds this and still writes code. KEY RESPONSIBILITIES • Lead the product and platform team and hire its next engineers; progress is measured in working software • Set the technical direction of the application, the platform and its on-premise deployment, and review the changes that matter together with a second engineer • Run the team on two-week cycles with working software at every review, in writing by default, in meetings only where writing is not enough • Agree with the research team what each side can rely on, and own the delivery into the business systems in use DESIRED QUALIFICATIONS • Has managed before and returned to building: led four to eight engineers, then held a staff or lead role, and now leads a small team while owning a hard technical area • Founded or was a founding engineer of a product several people use at once and hired its first engineers • On-premise software delivered into enterprise or government environments, through audit and security review • Managed a team that built on LLMs or agents in production, and can say how it was decided what was ready for release EXPECTED QUALIFICATIONS • T-shaped: deep in one domain, with working breadth in a neighbouring one • Structures a large, incompletely specified problem and drives it to a working result independently; settles a design disagreement by prototype • Led two to five engineers who shipped and operated a product in production, with a clear account of whom they hired and what those engineers did next • Work from the last two years on an application several people use at once, as code, a design document or a talk; still reads and reviews code daily; uses AI coding tools daily and verifies their output —— HOW WE WORK • Product engineering: we own what we build and run it in production • Small teams, two-week cycles, working software at every review • AI coding tools are part of the standard workflow WHAT WE OFFER • Founding-team scope • AI-augmented engineering environment • Access to on-premise Nvidia B200s • Flexible work environment PROCESS • Introductory call • Technical conversation • Practical session; the format is agreed with you In coding exercises, AI tools are allowed and expected. No LeetCode. WHO WE ARE New product organisation as part of a large semi-government in Abu Dhabi. International, ex-FAANG team. Completely greenfield, with a modern tech stack. —— REQUIREMENTS TO BE CONSIDERED • Clear written and spoken English; has reported technical progress to non-technical executives at fixed intervals • 6+ years in engineering, of which 2+ leading a team of engineers where work was accepted on measured results • Still coding: a product a user can open today, with a part the candidate designed and built; own code operated in production at a product company or a startup • Bachelor's degree in any field, or self-taught with a track record of open-source contributions RELATED TECHNOLOGIES AND CONCEPTS • Product: React, TypeScript, XState, replay • Platform: Kubernetes, Helm, on-premise and air-gapped deployment, secrets management (OpenBao or comparable), object storage • Services: NestJS or comparable, GraphQL, Redpanda or Kafka, PostgreSQL, graph databases • Integration: CRM and workflow systems, versioned interfaces, audit logging