The Role

We're looking for an AI Engineer to architect and deploy the intelligent agents that power our platform. You'll design autonomous systems that analyze customer signals, identify patterns, and make decisions; choosing the right AI techniques and models for each task. This is an on-site/hybrid position in Copenhagen with competitive salary and early-stage equity.

What You'll Build

• Intelligent agent systems: Build specialized AI agents that autonomously extract insights, classify customer signals, detect patterns, and trigger actions based on the data they process.

• Multi-model orchestration: Design systems that coordinate between different AI models and techniques. Use LLMs for reasoning and generation, embedding models for semantic search, classification models for categorization, clustering algorithms for pattern detection.

• Voice intelligence: Architect AI agents that conduct adaptive, context-aware voice interviews with customers, processing conversational data in real-time.

• Model selection and evaluation: Choose the right tool for each task, whether that's LLMs (Claude, Gemini), custom models, or classical ML techniques. Build evaluation frameworks to measure and improve agent performance.

• Production deployment: Move agents from prototype to production using Python, FastAPI, Pydantic AI, and GCP infrastructure (BigQuery, Postgres, Cloud Run)

What We're Looking For

• Technical skills: Experience building production AI/ML systems. Comfortable with Python, cloud infrastructure (GCP preferred), and working with LLMs in production environments.

• Shipping mindset: You care more about delivering value to customers than perfect architecture. Done is better than perfect.

• Generalist approach: You're willing to work across the stack when needed. This is an early-stage team where everyone does what's necessary.

• Clear communication: You can explain technical decisions and trade-offs to non-technical teammates.

• Startup experience: You've worked in fast-moving environments where priorities shift and you need to figure things out as you go.

Mindset We Value

• Owner mentality: you take responsibility for your work's impact

• Bias for action: you move fast, ship, and learn from real usage

• No ego: you're proud of scrappy solutions that get results

• Market obsessed: you care about solving customer problems, not politics or titles

• Organized and focused: you bring structure to chaos and keep momentum

Technology

• Backend: Python, FastAPI, Pydantic AI, PostgreSQL, BigQuery

• AI & ML: Large Language Models (Claude, Gemini), Embedding models, Classification algorithms, Clustering algorithms, Multi-model orchestration

• Infrastructure: Google Cloud Platform (Cloud Run), Production deployment pipelines, Real-time data processing

About the interview

1. Intro chat with a founder (CTO)

2. Paid take-home assignment based on a real design problem

3. 2–3 day paid work trial (in-office in Copenhagen) to collaborate with the team and assess culture fit ‍

Compensation

Competitive salary and early-stage equity