AI Engineer - Agentic & Autonomous Operations (m/f/x)

We’re looking for an AI Engineer to build the agentic capabilities at the heart of xHeron. You’ll help shape how our agents reason, act and learn, and build a company where AI doesn’t just support the work, but increasingly delivers it.

• Agent behavior & reasoning: Build and improve multi-step agent behavior, including reasoning, tool use, and human handoffs.
• Context & retrieval: Develop context and retrieval strategies that connect agents to relevant operational knowledge and reusable expertise.
• Evaluation & testing: Build evaluations and regression tests to measure decision quality, task completion, and failure patterns.
• Continuous improvement: Use production traces and operator feedback to improve models, prompts, and agent architecture.
• Production ownership: Ship and maintain production code alongside our CTO and engineering team, working closely with systems engineering on safe execution.

• You have strong software engineering foundations and can build reliable production software in Python.
• You have built a substantial LLM, automation, or decision system—not only experimented through chat interfaces. Direct agent experience is valuable, but strong adjacent experience also counts.
• You can connect intelligence to real work: selecting relevant context, making a bounded decision, using tools or APIs, and determining whether the intended effect actually occurred.
• You think carefully about when AI should act, wait, ask for help, or escalate. You understand that uncertainty, permissions, and failure handling are part of the product.
• You have shipped software that people use and have worked through testing, debugging, operational failures, and imperfect real-world data.
• You assess AI behavior systematically using representative test cases, traces, comparisons, production feedback, and clear definitions of success.
• You investigate ambiguous problems independently, explain trade-offs clearly, and turn decisions into working software.
• You bring useful expertise and an independent perspective. We value people who can transfer what they have learned from other domains and develop practical solutions to unfamiliar problems.

Around 2+ years of software engineering experience is a useful guide, not a hard requirement. What matters is the depth of what you have built, the decisions you owned, and your ability to learn.

• Your experience is limited to prompting, chat demos, or connecting an LLM API without owning the surrounding software.
• You prefer receiving a fully scoped specification rather than investigating an unclear problem and helping define the right solution.
• You are comfortable treating a plausible model response as success without checking whether the resulting action was correct and effective.
• You are not interested in owning evaluation, failure analysis, and production learning alongside feature development.
• You prefer narrowly bounded implementation work with stable requirements and limited responsibility for product or operational outcomes.

• Intro call (30 min): a conversation with Friedrich (CTO) about your background, what you've built, and why this role.
• Technical take-home case study: a short, real engineering problem, close to what you'd actually be building.
• Case study interview (1 hour): you walk us through your thinking, not just the final code.
• Culture fit (30 min): meet both Founders and make sure it's a fit both ways.