Make frontier modelsuseful, trusted, and safeacross people's health journeys.
Microsoft AI's Health team is hiring an Applied AI Lead to turn frontier models into Copilot Health — building rigorous health evaluations, architecting agentic LLM orchestration, and growing a team of Applied AI Engineers while staying hands-on. I bring a decade of high-agency, player-coach delivery, production agentic systems with eval harnesses (Claude-led, Gemini second), and a HIPAA clinical platform behind me — and London is where my family already is.
Eval-gated delivery. Agentic orchestration. Health at the core.
Engineers grown into leaders, not just features shipped
Weekly design and code review, 1:1 coaching, judgment over throughput — alumni I mentored now lead engineering in Norway (2) and at two top local firms, with others coached into graduate study in Canada and a UX design career in Germany. Leading and growing a team of Applied AI Engineers while staying a credible authority on evals is the exact loop I run.
Together we make frontier models useful, trusted and safe across people's health journeys — with evaluation and orchestration rigorous enough to earn that trust.
I build the systems that turn frontier models into products people can trust — then I keep raising the bar on evaluation, orchestration, and how the team ships.
Fauzul — on why Microsoft AI, Health
Every verdict above maps to shipped work. Pick one and challenge it.
Questions a sharp hiring loop would raise.
The objections a sharp Applied AI Lead loop would raise — including the AI-stack one — answered straight.
No, and I won't paper over it. My hands-on production AI has been Claude-led with Gemini second — I pick model and harness per task, not by vendor loyalty, and haven't had reason to run OpenAI's models in production yet. But the value here is the discipline, not the vendor: harness and context engineering, grounding evals, tool use, retrieval, agentic multi-step systems, and benchmarking are model-agnostic and transfer to any family. I already blend model classes and families per task — Claude, Gemini, Kimi via OpenRouter, on-device Gemma — so getting productive on Copilot Health's stack is a ramp measured in weeks, not a re-education.
The role asks for significant ML research. You're an applied-AI engineer, not a researcher — right?
Correct, and I won't pretend otherwise. I ship applied LLM systems and evaluation harnesses; I have not published ML research. What I do bring is research-adjacent grounding — the Google × Kaggle 5-Day AI Agents Intensive and Microsoft's Azure ML AutoML curriculum — plus the ability to turn cutting-edge technique into shipped product fast. On this team I'd own the applied build and health-eval design, and partner with research-track colleagues where formal research is the right tool.
Your leadership is founder/CIO at a studio, not a big-tech TLM. Can you lead an Applied AI Engineer team at Microsoft's scale?
I have 8+ years of software engineering and have managed people for 7 of them while staying hands-on — formally Engineering Manager 2022–2024, then CIO — leading a 22-person cross-functional core and dedicated client pods, including hiring and HR for a Norway team. Alumni I mentored now lead engineering in Norway (2) and at two top local firms, with others coached into graduate study in Canada and a UX design career in Germany. The JD explicitly says a strong tech lead ready to step into a TLM role will be considered; I am past that bar, and I stay hands-on rather than drifting into pure management.
Have you built health-specific LLM evaluations before?
I've built the two halves this role fuses: a HIPAA clinical platform ( — patient-data pipeline and EHR) and grounding-eval pipelines that gate production (, ). Health-specific benchmark suites for accuracy, safety and utility are what I would build first — on real eval discipline and real health-domain context, not from a standing start. That combination is exactly why this seat fits.
Do you have a completed CS degree?
Field of Study: Computer Science & Engineering at North South University (2012–2015). I do not claim a completed degree. My qualification is experience-based — a decade of shipped applied-AI systems and 8+ years of engineering leadership are the operative credentials, and strong applied Python and LLM engineering back the technical bar.
This is 4 days a week in-office in London. Are you genuinely relocating?
Yes — and it isn't a cold bet. My sister lives in London, so it's a real personal base, and my professional history in Europe is genuine: multi-year London B2B and audio-engineering clients, a 6+ year Zürich engagement (, acquired by Loopcloud 2026), and a Norway fintech pod (Frontgo, Vipps). Four days a week in-office is exactly where I want to be for this seat.
Claude-led, model picked per task, not by vendor loyalty.
The stack and receipts behind the claims — Claude-led, Gemini second, model picked per task; eval harnesses and agentic orchestration as habit.
let's make Copilot Health_safe enough to trust.
London is where I want to build, and that is a professional judgment before it is a personal one. It is the densest frontier-tech hub outside the US West Coast — the place where the AI labs, the banks, the NHS and public-sector programmes, the scale-ups and the enterprise buyers all sit inside the same hour. For an engineer who works *embedded with customers*, that concentration is the whole point: more real businesses to talk to, more industries in one commute, and the fastest way to keep learning how technology and business actually move each other. The energy is real too — you feel the pace of the city in the work. It is also a genuine personal base: my sister lives there, and my delivery history in Europe is real — multi-year London client work, a 6+ year Zürich engagement (Jamahook, acquired by Loopcloud 2026), and a Norway fintech pod (Frontgo, Vipps). See London for the full picture. This seat is 4 days a week in-office and I want that — being in the room, in that city, is the point.
Four other Microsoft seats, each in its own register.
A personal application fit page, not affiliated with or endorsed by Microsoft. Copilot / Azure / Fabric / ISD references are illustrative of the role's own team and domain — no confidential or internal Microsoft information is shown.