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Open nowPosted 76 days ago

AI Engineer

Appfarm AS1 open role

Where
Oslo
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Your applicationOpen nowAI EngineerAppfarm AS · Oslo

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  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 76 days ago

The posting

We're expanding the team and looking for an engineer who wants real ownership of how we build out Appfarm AI. Some days, that means evaluating the latest foundation models. Most days, it means building the platform around them - improving the builder experience inside Appfarm Create and developing the AI building blocks customers use to ship intelligent applications, agents, and automations. <br><br>You'll sit in our platform team, a solid engineering group that works closely with product and design.

Who we're looking for

  • You've shipped real AI features. You've put LLMs into production - prompts, RAG pipelines or agentic systems - and you know the difference between a demo that impresses and a feature that holds up over time.
  • You're a strong engineer with solid hands-on experience. Comfortable across the stack and able to own delivery. Our stack is TypeScript, Node.js, React/Redux, and Google Cloud.
  • You use agentic coding tools daily. This is directly relevant to the product you'll be building.
  • You're pragmatic. You make architectural choices that don't lock us into a single vendor, and you'd rather smartly compose existing models than build from scratch.
  • You take ownership. Reliability, cost, and how things fail matter to you as much as how cool something is.

What you'll be doing

  • Integrate and evaluate LLMs as the landscape evolves. We build on Anthropic models today, but we want someone who can navigate what comes next.
  • Make the AI builder genuinely useful - so users can describe what they want and get working applications back, with the visual transparency that sets us apart from generic AI code generators.
  • Design and build agentic building blocks and MCP integrations that customers compose into their own AI-powered solutions.
  • Set up evals and observability so AI features work reliably in production - not just in demos.
  • Solve the hard production problems: reliability, cost, latency, and graceful failure when agents go deep.
  • Partner with product and design to package AI features that feel simple to end users but hold up under real enterprise demands.
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    The review screen in CV Rocket: how each CV was read, round by round.

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