AI Engineer

What we offer...

• 💰 Competitive salary - our salaries are in the top percentiles of the Barcelona startup scene.

• 📈 Equity - By joining the company when the team is so small, you're helping us set the foundations of our future success. We're asking you to come on an adventure, so if we find a treasure, we want you to get a piece.

• 🤖 Generous token spend policy - We expect our team members to work at the frontier of what's possible with AI. We expect spending, not saving, at the moment

• 🏖️ 30 days holiday allowance - Recharge whenever you need to.

• 🍏 Health coverage - Alan partnership covers half your medical insurance, anywhere you are.

• 💳 Tax-smart savings - Cobee by Pluxee for meals, transport, nursery. Keep more of what you earn.

We're HappyScribe, a profitable, 100% bootstrapped AI company based in Barcelona.

We built one of the web's most accurate multilingual transcription platforms, trusted by hundreds of thousands of users each month. That product funds our freedom to create what's next-no investors, no burn rate, just focus.

Now we're taking that same tech and expertise to a bigger frontier: turning conversations into intelligence. We're building the layer where speech becomes memory, insights become action, and teams work with more clarity and speed.

You'd be joining a team of ~17 people, close-knit and pragmatic. Some of us are scaling a mature, revenue-generating platform. Others are prototyping new products that push the limits of speech and agentic AI.

We move fast but think long-term. There's room here to shape, ship, and own real products - not pitch decks.

About the role...

We're looking for an AI Engineer to work on the AI layer that powers HappyScribe Intelligence features. You will work on building features that bring together LLMs, speech models, and retrieval systems to address real user problems.

This role is for builders obsessed with making AI actually work - engineers who'd rather ship a clever prompt chain that solves a real problem than debate model architectures in Slack or over-engineer multi-agent frameworks that become quickly obsolete.

What you will do...

• Own AI features end-to-end - from problem discovery to prompt design to production. You'll build the systems that turn conversations into intelligence: summaries, search, actions, memory.

• Build and maintain our evaluation framework. You'll design evals that actually catch regressions, iterate on prompts with confidence, and keep quality high as models change under us.

• Optimize our AI infrastructure for speed, cost, and reliability. Provider routing, caching strategies, chunking approaches, latency budgets - you'll own the trade-offs.

• Stay dangerously current. The field moves weekly. You'll bring new techniques to the team and know when a new model or approach is worth the migration cost.

• Ship with the product team. You'll work closely with designers and engineers to integrate AI features that feel native, not bolted on.

• Example projects:

  • Design and ship semantic search across transcripts using embeddings and hybrid retrieval.

  • Build an agentic system that turns meeting notes into drafted emails, tasks, and follow-ups.

  • Create a prompt evaluation pipeline that catches quality regressions before users do.