We’re hiring

Build AI tools that get used.

Learn the proven PE playbooks that actually get implemented.

We turn full-stack devs into tier-1 AI engineers who own a real system end to end, taught by the people behind a 500k-practitioner learning platform.

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Join a team of engineers, investors, operators, and ex-founders

The opportunity ahead

The real AI opportunity is in the mid-market, not the Fortune 500.

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SME economics

AI has the biggest impact in SMEs.

Large enterprises run at high efficiency with ‘fortified’ IT and slow procurement. SMEs have obvious bottlenecks and short feedback loops. The marginal impact of every AI deployment is not only bigger, you see it in the P&L.

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Repeatable playbooks

SMEs share the same bottlenecks.

Procurement, document workflows, sales pipeline triage, customer service. We’ve built playbooks for each. Every new engagement compounds on the last.

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PE as adoption driver

Adoption is structural, not nice-to-have.

Inside PE-backed portcos, weekly operating cadences, focused KPIs, and CEO incentives ensure tools we build actually get used. The work ships and gets adopted by design.

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No legacy drag

You’ll work at the frontier — shaping new playbooks with the latest technology.

We don’t maintain a long-lived product platform. Each engagement is a fresh deployment, so you’re using the best AI tooling and defining the most effective use case every time.

Open role

Deployment Strategist.

Translate bottlenecks and workflow pain points into AI-enabled workflows. Own client engagements at PE-backed portcos end-to-end.

Who you are

Consistently performed at a high level in tier-1 institutions
You take pride in measurable impact in real companies, not slide decks
Comfortable owning client relationships and engagement outcomes
2+ years experience

What you'll do

Own deployment engagements at PE-backed portcos
Map workflows, identify high-impact automations, scope solutions
Run delivery from kickoff to live system
Stakeholder management across PE partners, portco C-level, and technical teams

What you'll learn

PE playbooks that actually get implemented
Work alongside top-tier PE partners and operating partners at leading funds
Use the latest AI tools to stay at the forefront of the field
Proven workflows across procurement, sales, finance, and document automation

Open role

AI Engineer.

Build production AI with the latest tools. We turn full-stack devs into tier-1 AI engineers through our best-in-class learning platform.

Who you are

2+ years as a full-stack developer
You work fluently with modern dev tools (TypeScript, Python, React, Postgres, Docker, Git)
You want to learn how to use AI tools most effectively
You regularly use AI coding tools (Cursor, Claude Code, Copilot, or similar)

What you'll do

Build production AI systems inside PE-backed companies
RAG pipelines, agents, document automation, custom tooling
Pick the right model, framework, and tradeoffs each time
Own deployments end-to-end

What you'll learn

Direct upskilling from the authors of Building LLMs for Production (10k+ copies sold)
The frontier of what works in production AI
Internal playbooks across procurement, sales, finance, document workflows
How to ship AI inside real businesses, rarer than it sounds

What you get

Why this team.

Globally distributed, headquartered in London.

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Education and deployment, one firm

200k+ newsletter readers. 100k+ community members. 500k+ practitioners taught since 2019. Our book is used inside enterprise AI teams; our courses run on O’Reilly. The path runs community → Learning → Deployment pod: you join the pods that own real systems end to end.

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The people

Our team has a breadth of experience across leading companies, having seen the PE value-creation and AI tool-building process end-to-end.

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Latest tools, always

No legacy platform to maintain. Every project uses the best AI tooling available at the time of building.

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Proven playbooks

We've shipped AI inside multiple PE portcos. We know what moves the needle and what doesn't.

How recruitment works

Five conversations.

We read every application individually, which takes time. We also receive more applications than we can interview. From first call to offer typically takes 2–4 weeks. We keep candidates updated at every stage.

01

Initial conversation

45 min

A get-to-know-you call. We’ll walk through your experience using the STAR framework, what you’ve shipped, and what motivates you.

02

Technical assessment

1 hour

For Engineers: a live coding and AI architecture session.
For Strategists: a case study on how you’d approach a real PE-backed deployment.

03

Project presentation

1 hour

In-person or video.
15 min: you walk through a recent project you’ve owned.
45 min: Q&A with senior leaders.
For Strategists we look for presentation skills, executive presence, and how you think.
For Engineers we focus on technical capability and how you think.

04

Cultural fit

Senior team call

A relaxed conversation with senior members of the team. Really just a chance to make sure this feels like the right home for you, and that we’d build well together.

05

The offer

If the fit feels right on both sides, we’d be delighted to welcome you to the team.

FAQs

Frequently asked questions.

We try our best to answer every question within a few days. Unfortunately we receive more emails than we have time to review, so please have a look below first; we’ve covered the most common questions. If yours isn’t answered here, do send it through afterwards.

Does Towards AI use AI to assess job applicants?

No, we don’t. Every application is read by a real person on our team. We think that’s the right thing to do, especially for an AI company. The work matters too much to outsource the first impression of you to a model.

When should I expect to hear back after I apply?

We aim to reply to everyone within a week, one way or the other. Sometimes it takes a little longer when we’re working through a wave of applications. If you haven’t heard from us by then, please don’t hesitate to nudge us.

Can I apply for more than one open role?

We currently have two open roles: AI Engineer and Deployment Strategist. Pick the one that feels most like you, and apply there. If we think the other role might suit you better, we’ll bring it up during the process.

Does Towards AI give application or interview feedback?

If you make it to the interview stage and things don’t work out, we’ll do our best to share useful thoughts within a few days. We genuinely wish we could give feedback to everyone who applies, but the volume makes that impossible. We’d rather be honest about that than promise something we can’t deliver.

Can I reapply if I was unsuccessful the first time?

Yes, though we’d gently suggest waiting at least a year before reapplying for the same role. If we come across a different opening that feels like a better fit for your background, we’ll reach out. Following our team on LinkedIn and X is the best way to catch new roles as they open.

Does Towards AI pay for travel costs for on-site interviews?

Most of our interviews happen over Google Meet or Zoom, so travel usually isn’t needed. On the rare occasion we invite you to meet in person, we’re happy to cover reasonable travel and accommodation. Just let us know what you need.

I’m a recruiter. Can I help Towards AI find more talent?

Thanks for the offer, and we mean that genuinely. For now we’ve built our own trusted networks for hiring, so we rarely need external support. If that changes, we work with a small list of preferred partners that we review regularly.

How to apply

Ready to build?

Send your LinkedIn, CV, and a short note on why this role interests you. We read every email and reply within a week.

Email denis@towardsai.netarrow_forward

Competitive comp + equity.