A founder-built, full-stack engineer who ships custom AI software on the customer's own infrastructure.
Forward Deployed Software Engineer is the work Fauzul has been doing for a decade — embedding with customers, scoping fuzzy business problems, and building the custom software that actually solves them. He is a founder who has shipped products from scratch across health-tech, fintech, HR-tech, hospitality and export, and over the last year that became shipping LLM-powered software into real client stacks: a natural-language CMS running in production for a 26-year-old export house, plus agentic 0→1 builds (, , ) using A2A, MCP and n8n. He designs reusable abstractions and design systems that scale delivery across a portfolio, codes side-by-side on the customer's infrastructure, and treats reliability and compliance (HIPAA, GDPR, OIDC/RBAC) as product surfaces — exactly the build-effective-software-on-OpenAI's-APIs profile the Forward Deployed Engineering team needs in London.
Custom LLM software, already in production
Forward Deployed Software Engineer is the work I'd already been doing — embedding with customers, scoping fuzzy problems, and building the software that solves them, on their own stack. Over the last year that became shipping LLM-powered software into production.
An LLM-powered CMS, running in a client's production stack
For — a 26-year-old Dhaka export house — I skipped the traditional headless CMS entirely and built custom software instead: the client expresses the change they want in plain natural language, the model turns that into a pull request, and CI/CD ships it to production at the edge. Effective custom software that leverages an LLM to solve a real customer problem — the deployment pattern is model-agnostic, and the FDSWE craft is what makes it land.
Natural-language intent → model-authored PR → automated CI/CD deploy to production at the edge.
Reusable abstractions over one-offs: the component libraries, multi-tenant architecture, and OIDC/RBAC auth backbone every product ships on — built once, well, to scale delivery.
Agentic 0→1 in public: (goal-first intros), (autonomous briefings via n8n + LLM steps), — multi-agent reasoning with A2A and MCP.
Full-stack on the customer's infrastructure — React/Next on Go/Node/TypeScript with Postgres — with reliability and compliance (HIPAA, GDPR/VAT, OIDC/RBAC) built in.
LLM-powered CMS — in production
Custom software: natural-language requests become model-authored PRs and automated deploys for a 26-year-old export house.
Reusable abstractions — ELO platform
Component libraries, multi-tenant architecture, and an OIDC/RBAC auth backbone every product ships on — built once to scale delivery.
Embedded delivery — Frontgo · Skytracks
Built and led from-scratch engineering teams to production on clients' own infrastructure, integrating Vipps payments and partnering with client CTOs.
Point by point
The role is Forward Deployed Software Engineer — building effective custom software that leverages OpenAI's APIs to solve strategic customers' hardest problems, designing abstractions that scale delivery across every Forward Deployed engagement, and coding side-by-side on the customer's infrastructure. Here's how a founder's decade of end-to-end, customer-facing delivery maps onto each point.
Embed deeply with strategic customers to understand their business challenges and technical requirements in detail.
Ten years dropping into ambiguous enterprise environments across London, Zurich, Oslo, Sandnes, Dubai, Florida and Quebec — translating raw requirements into granular engineering tickets and leading delivery by example. Comfortable in the room with both engineers and executives; the embedded, on-site mode is the part of the job he wants, not a cost he tolerates.
Design, architect, and develop full-stack solutions using an experiment-driven, iterative approach — with a bias for action.
End-to-end builder who still writes the code: polished frontends (React, Next.js, Angular, Tailwind) on Go/Node/TypeScript backends. Ships 0→1 fast and iteratively — solo-built on Bolt.new during the World's Largest Hackathon, shipped in a one-week sprint — validating with real users before over-building.
Build effective custom software that leverages LLM APIs to solve real customer problems, and design abstractions that scale speed and quality of delivery across engagements.
Ships LLM-powered software that does real work — a natural-language CMS in production for — and is a systems-thinker about reuse: architected the Storybook component libraries, multi-tenant component architecture, and the OIDC/RBAC auth backbone that all products are delivered on. Wrote the pattern paper on monorepo multi-project components precisely because abstractions are how a small team scales delivery across a portfolio.
Prepare detailed scopes of work and project plans for both proof-of-concept prototypes and full production deployments.
Owns the use case from ambiguous brief → POC → CI/CD pipeline → production. A decade of client delivery means scoping, sequencing, and planning POCs and production rollouts is native — and he validates the problem before committing capital (ran four pop-up events to test a restaurant brand before building).
Work hands-on with customers' technical teams as a technical expert and trusted advisor, coding side-by-side to drive projects to completion on their infrastructure.
Has hired and led dedicated engineering teams embedded with clients (built a 0→production team for Norway's Frontgo fintech, integrating Vipps payments) and partnered directly with client CTOs (Skytracks, Canada). Earns trust by shipping on the customer's stack, then hands over operations with absolute trust.
7+ years of professional full-stack engineering at product-driven companies; former founder / early engineer who has built a product from scratch (a plus); experience with relational databases (Postgres / MySQL).
9+ years full-stack and co-founder of — has built products from an empty canvas to production many times over. PostgreSQL is a core part of his stack across products (alongside Firestore, MongoDB, Redis, pgvector). The founder/early-engineer 'built it from scratch' signal is his entire career.
Collaborate with Product, Research and Applied teams for actionable feedback, and codify best practices into internal knowledge bases to scale the Forward Deployed Engineering function.
Learns and teaches in public — pattern papers on Medium (monorepo components; typing-speed & developer productivity), a GitOps webinar series, and reusable playbooks built so others can ship. Naturally closes the loop from the field back into shared tooling and documentation.
Strengths & honest gaps
A founder who builds products from scratch
Co-founded and shipped 0→1 across five verticals and multiple continents — exactly the 'former founder / early engineer who built a product from scratch' the role calls a plus. Solo-built and shipped in a week: bias for action is the default, not an aspiration.
Full-stack, on the customer's infrastructure
Writes the frontend, the backend, and the glue — React/Next.js on Go/Node/TypeScript with Postgres — and embeds to code side-by-side on the client's stack, having built and led teams to production for clients like Norway's Frontgo and Canada's Skytracks.
Abstractions that scale a delivery function
Architected the component libraries, multi-tenant architecture, and OIDC/RBAC auth backbone that every product ships on, and wrote the pattern paper on it. Treats reusable abstractions as the way a small team scales speed and quality across many engagements — the core of the FDSWE mandate.
LLM software shipping in production, honestly framed
A natural-language CMS turns plain English into model-authored PRs and automated deploys for a real client today; plus agentic 0→1 builds (, , ). The deployment skill is model-agnostic — and he's candid that his shipped AI has been Claude-led, eager to go deep on OpenAI's APIs.
Production depth on OpenAI's own API and tooling specifically (shipped LLM work has been Claude- and Gemini-led).
2–4 weeksAPI integration is model-agnostic — the same prompt/context design, tool-calling, retrieval, and evaluation discipline he already uses ports directly. He closes it fastest by building real customer software on OpenAI's API from week one, carrying his existing CI, typing, testing and observability habits across.
What else I bring
Strategic partner, developer champion, and technical operator. Fauzul’s background as a co-founder and CIO unlocks value far beyond the standard engineering parameters.
Developer Advocacy & Platform Champion
Fauzul has a proven track record of writing in public (blogging, tutorials) and maintaining a 900+ day learning streak. He is ready to act as a developer champion inside strategic customer teams, build high-fidelity demos/guides that highlight OpenAI's API capabilities, and help customer devs ship agents with confidence.
Founder-Operator Strategy Partnership
Having served as co-founder and CIO of multiple ventures, Fauzul operates with strong commercial and product empathy. He knows how to translate developer and customer friction directly into prioritized product requirements and feed those insights straight back to OpenAI's Research and Product teams to shape model and API roadmaps.
Compliance & Enterprise Gating
With deep compliance delivery experience (HIPAA pipelines at EKAGRA, GDPR/VAT structures at Jamahook), Fauzul speaks the language of corporate risk, privacy, and architecture reviews. He can proactively help customer security officers audit and approve OpenAI's trust boundaries, accelerating the path to production.
Candid answers
Candid answers — why a founder wants the FDSWE seat, the honest read on shipping Claude rather than OpenAI's API in production, how he designs abstractions that scale a delivery function, and how he's set up for hybrid London plus heavy travel.
The role is about building software on OpenAI's APIs, but your production LLM work has been Claude-led. Why you?
I'll be honest rather than overstate it: what I've shipped in production has been Claude- and Gemini-led, and that integrity matters to me. But the FDSWE job is building effective custom software that solves a customer's problem — discovery, scoping, full-stack build, coding on their infrastructure — and wiring an LLM API into that is model-agnostic: the same prompt and context design, tool-calling, retrieval, and evaluation discipline ports straight across. I've already put an LLM into a client's production stack and shipped agentic products in public. I'd be building real customer software on OpenAI's API from week one, and I'd rather be the engineer who's candid about where he's coming from and ramps visibly than one who oversells it.
You co-founded and run your own product engineering venture firm — why step into a Forward Deployed Software Engineer seat?
Because FDSWE is the work I love most, stripped of the agency overhead. As CIO my role drifted into running a client-services business; the part that lights me up is being in the room with a customer, turning an ambiguous problem into shipped software on their stack. OpenAI lets me do exactly that with frontier models behind me — and the 'former founder who built a product from scratch' the role asks for is literally my last decade. I'd rather build at that frontier from the inside than keep grinding it from the outside.
How do you design abstractions that scale delivery across many engagements without over-engineering?
I start from the concrete problem and only abstract once a pattern has earned it — but I've done this at portfolio scale: the component libraries, multi-tenant architecture, and OIDC/RBAC auth backbone every product ships on came from spotting the same need across clients and building it once, well. For a Forward Deployed function that means reusable building blocks, scopes-of-work templates, and playbooks captured from real engagements, so the second deployment is faster than the first. I wrote the pattern paper on exactly this because it's how a small team scales speed and quality.
Can you really code side-by-side on a customer's infrastructure as a trusted advisor?
Yes — it's how I've worked for years. I hired and led a from-scratch engineering team to production for Norway's Frontgo (integrating Vipps payments) and partnered directly with client CTOs like Skytracks in Canada. Embedding on someone else's stack, earning trust by shipping, and then handing over operations is the core of what I do. Being the technical expert in the room with the customer's engineers is the part of this role I'm most looking forward to.
This role is hybrid in London (3 days/week) with travel up to 50%. Are you set up for that?
Yes — I'm intentional about basing this chapter in London (my sister is there and I've supported Arsenal since 2003, so it's a genuine, durable move), comfortable on a 3-day in-office cadence, and I treat heavy customer travel as core to deploying well rather than a burden. I've delivered for London, Zurich, Oslo and Sandnes clients for years; I relocate as soon as the UK Skilled Worker visa processes and start on London hours from day one.
The stack & the builds
The stack and the builds that prove it — full-stack systems, agentic pipelines, relational-DB-backed products, and LLM software already running in a client's production stack.
Ready to deploy frontier AI?
Intentional about relocating to London, United Kingdom — ready for the hybrid office cadence and on-site customer travel from day one.