Appfarm · Oslo, Oslo, Norway ·
Builds and maintains Appfarm’s AI platform, integrating LLMs (e.g., Anthropic) into production features like agentic applications and automations, ensuring reliability, cost-efficiency, and seamless user integration within Appfarm Create.
userpilot · Dublin, Dublin, Ireland
hilberts · Türkiye
Sendbird · Seoul, South Korea
Proofpoint · North Carolina
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.
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.
sarvam · Bengaluru