Agent Harness Engineer; On-site

Overview

You're the person who makes Viktor do more things, for more customers, more reliably. You've built agents before (runtime, tools, memory, evals) and have opinions about what makes them work. You ship the day you write the code and reach for AI‑assisted development by default. If you haven't built an agent, this isn't the role.

Viktor runs a persistent Linux sandbox for every workspace and writes its own Python to drive 3,000+ integrations, from Salesforce to Stripe to Shopify. That's 1.5M+ tool calls a day against real customer data, and the curve is steep. We’re betting one general agent, fluent across everything a company runs on, beats a stack of narrow tools. An agent that impresses in a demo and one that 25,000+ teams trust with their real work are different machines, and the distance between them is the whole job.

• Build the agent runtime: the loop where it plans, acts, and verifies its own work instead of declaring success it didn’t earn.
• Make the agent fluent with tools: composition across many integrations, recall, and the skill files that keep the right functions at hand.
• Grow what the agent can do: memory it can trust, skills it writes for itself, work it runs on its own.
• Make it measurably better: evals, catching regressions, and turning every failure into a fix.
• Ship product: features that reach users through Slack and Teams within hours. Whatever needs building. Small team, large surface.

You ship to production every day, and the changelog has your name on it. When Viktor breaks at 3am, you can fix it because you understand the system end to end. This role doesn’t work without agentic coding fluency: if AI‑assisted development isn’t already how you work, you’ll be behind on day one.

• You've personally built or significantly modified an AI agent harness, and can describe the trade‑offs you made.
• You've made an agent reliably close the loop: tests, linters, type checkers, browser verification, whatever stops it hallucinating success.
• You've built custom skills, commands, CLIs, or MCP servers to make your own agentic coding faster.
• Agentic coding is your daily workflow, and you've stress‑tested models and harnesses across the frontier.
• Systems thinking. You make hard technical trade‑offs and design for how things break at scale.
• Speed, with the bar up. You ship today, not Thursday.
• Range. Agent runtime to React component to deployment script in an afternoon.
• Genuine interest in how AI works. You’ve read the papers and have opinions about evals.
• Onsite. This is an in‑office role, not remote.

• Previous AI engineering experience: agents, harnesses, eval infrastructure.
• Previous founder or early‑stage builder.
• Open source contributions to the AI tooling we live in.
• Tech:
  Type Script/React on the frontend, Python on the backend and agents, Modal for infrastructure. You don’t need all of it coming in, but you need to learn fast.

Top‑of‑the‑market salary and the kind of ownership that only exists at this stage. The best work happens when you’re in the room. Munich, New York, Dublin, and Warsaw. Remote for some roles.