London · full-time · reports to the co-founders. You will own AI deployment engagements at private equity-backed portfolio companies and finance firms end to end, from the first scoping conversation to a live system the client's team runs without us. This is a technical strategist role: you design the systems you scope, and you build with AI every day.
- -Scope engagements with leaders and end users: workflow mapping, the problem statement, the automations with the most impact, calibrated to hold-period economics.
- -Write the proposal that goes into the contract and the PRD that translates it for the engineers; build the pre-sales demos and POCs yourself, with AI tools.
- -Run delivery from kickoff to live system, usually two engagements at a time: tickets, PR reviews, user demos, the launch decision with the sponsor, adoption and renewal.
- -Manage stakeholders from PE partners to portfolio-company executives and technical teams, and teach non-technical executives what models can do today.
- -Build the firm's PE and finance playbooks: diligence frameworks, value-creation plans, executive workshops, reusable AI assets.
Typical engagements: value-creation plans for portfolio companies, finance reporting and reconciliation, tender intelligence, investment research and due diligence agents, document and workflow automation.
We work in small pods: a deployment strategist, two AI engineers and an AI architect in the background; the strategist owns the client and the scope, the engineers own the codebase and the architecture. Each engagement starts with leaders and end users to find the highest-value use cases, agrees data access and controls with the client's IT and security teams, then builds with regular user demos and either keeps running the system or hands it over to the client's team. Most work runs from our London office; on the largest engagements, people go forward-deployed at the client site for kick-off, key build phases and rollout.
Daily, fluent use of Claude, ChatGPT and similar tools across most of your output is non-negotiable. You also build: you have shipped something with Claude Code, Codex, Cursor or an equivalent in the last three months, you can wire an API or an MCP server, and you turn your expertise into reusable assets our engineers can run in production. Part of the value you deliver is teaching clients to work the same way.
An operator with commercial judgment who takes pride in measurable impact at real companies and builds with AI themselves. Three backgrounds tend to fit: the strategy consultant or PE operator who became hands-on technical; the technical product manager who presents at C-suite level; the customer-side engineer who can run a room and still open the repo.
Required
- -Something shipped with Claude Code, Codex, Cursor or an equivalent in the last three months; you can wire an API or an MCP server.
- -Given a new business problem, you can choose between a workflow, an agent, retrieval or plain software, sketch the system from data to UI, and say where it breaks.
- -Ownership of client relationships and outcomes; the instincts to scope an engagement, defend a price and structure a multi-quarter programme.
- -Writing that holds up in front of a board; typically 5+ years in strategy consulting, private equity, product or customer-side engineering.
Useful: PE or portfolio-operations experience; sector depth in financial services; a senior network across PE and finance; French, German or Italian.
A senior role: you own engagements and the proposals behind them. The next step owns a portfolio-wide programme and the renewal book.
- -Location: our London office, fully in person, with flexibility when you need it; some travel to clients in the UK and abroad.
- -Right to work: you need the right to work in the UK before you start; for exceptional candidates we can sponsor a visa.
- -Pay: a market-rate base calibrated to the level, plus a potential performance bonus.
- -Tools: team plans on Claude Code and Codex; Granola, Notion, Slack and Linear; the Towards AI curriculum.
- -We hire for talent, curiosity and character, and want a team where people of every background can do their best work.
Two to three rounds depending on the role, 45 minutes each; we aim for about three weeks from first conversation to offer: a conversation with two co-founders about what you have built and how you build with AI; a take-home case capped at five hours, delivered as a repo, then a debrief where you present it (no live coding tests); for strategists and enablement leads, a live case or workshop in our London office where possible; then a call with one of our co-CEOs to make the offer, subject to two references and right to work.
Towards AI Deployment is the build side of Towards AI Inc., the AI deployment and education firm founded in 2019 (500,000+ practitioners trained, a 200,000+ newsletter, the O'Reilly book Building LLMs for Production). We go into private equity firms, portfolio companies and finance firms and ship AI systems they can actually run: not pilots that quietly die, but tools that hold up in production and change how the business works. We are 20+ people, with experience from Palantir, BCG, UBS, J.P. Morgan, SAP and Mila.
Apply through the form on our website. A link to what you have built and a few lines on your most useful AI work tell us more than a long CV.