AI Engineer

Mercura is building AI software for the backbone of our economy.

We are one of the fastest growing companies from YC’s W25 batch and raised a heavily oversubscribed round at one of the highest valuations in our cohort. After surpassing $1M in ARR in under a year, we are looking for team members ready to go all-in to help us reach our next milestone: $10M ARR by the end of 2026.

One of our co-founders, Lukas, grew up in a trades family that has been active in the construction industry for over 115 years. Having worked on the construction site himself, he learned first-hand how slow and manual quoting still is in the industry.

In an era where AI becomes ubiquitous, we set out on a deeply personal mission: bring AI to the backbone of our economy - to the companies that keep our world running.

As an AI Engineer, you will play a key role in building AI systems end-to-end. This is a fast-paced, hands-on role for engineers with high agency, strong technical depth and founder mindset. You’ll apply the latest technologies in NLP, LLMs, and AI agents - far beyond prompt engineering - while working alongside a team of the most stellar engineers.

If you’re a passionate builder who excels at the intersection of LLMs, NLP, AI, data engineering, and full-stack development, this is your opportunity to shape how users interact with AI.

What you will be working on

• Work with embeddings and fine-tune LLMs for classification and reranking
• Optimize algorithms for product search
• Apply RLHF & DPO to align LLMs with human feedback
• Build data & ML pipelines to process large-scale unstructured data efficiently
• Build, deploy and optimize AI agents end-to-end
• Own the architecture and design of AI systems
• Collaborate with other stellar engineers across the full stack

What we're looking for

We are looking for stellar engineers with a strong background in LLMs, AI & ML - and the potential to grow and lead teams in the future.

Technical skillset:

• Strong experience with NLP, LLMs, Embeddings, ML, and AI agents that goes far beyond prompt engineering (e.g., LoRA, tool calling / structured outputs, evals, retrievers / rerankers, RLHF/DPO)
• Proven track record of architecting and building complex, production-grade AI systems
• Demonstrated experience in scaling data & ML pipelines from a few users to thousands of users
• Experience with full-stack software engineering (React, Typescript, Python) is a plus
• Cloud & DevOps: Experience with containerization (Docker, Kubernetes), cloud infrastructure (Azure/AWS/GCP), and infrastructure as code (Terraform) is a plus

Commitment & mindset:

• High agency & ownership: You develop new ideas and drive them in execution under minimal guidance
• Mission-driven: Your job is part of how you define yourself. You treat your work as a top priority, and you’re fully committed to achieving ambitious goals amid uncertainty
• Product mindset: You demonstrate product thinking on a deep level and solve problems end-to-end
• You’re excited to iterate quickly and build software in a fast-paced startup environment
• You want to work in-person in Munich with a higher intensity than in a 9-5 job

Leadership & communication:

• You naturally take responsibility and enjoy leading teams
• You’re one of the strongest engineers in the team and make everyone else better
• Everyone can come to you for advice on how to fix their hardest problems
• Clients respect your presence & technical expertise

Company Perks

• Free team dinner (up to 4x/week)
• UrbanSportsClub membership - join our team workouts 3x/week
• Easy relocation to Munich — our office is located in the Werk1 Startup Incubator, where you can rent a 1-bedroom apartment right next to the office for just €750/month
• Real shares in our company with the most favorable tax treatment - no VSOP/ESOP
• Access to any AI or productivity tools you need

The target total compensation (cash+bonus+equity) for this position is €90,000-€200,000 annually. Actual offers and compensation are based on specific job duties, experience, performance, total rewards structure, and other considerations.

Step 1: Intro call

Casual intro meeting with one of the founders to get to know each other and introduce Mercura

Step 2: Technical interview

The technical interview consists of two parts:

1. A take-home exercise, including a short presentation and a live-coding session.
2. A system design interview.

For the take-home exercise, we’d provide you with a task. You’ll have 2–3 hours to complete it, focusing on data and AI engineering (e.g., NLP, embeddings, LLMs). The challenge will be based on a practical problem we’ve encountered in our day-to-day work, so it should give you a realistic sense of what the role involves.

Later, you’ll present your results to us. The presentation will include a brief algorithmic live-coding challenge, similar to a competitive programming task.

Step 3: Personal Fit

Meet another co-founder to get a feel for our culture and working style.

Step 4: On-Site

Work alongside the entire team for a day on-site from our Munich office to fully immerse yourself in our culture and collaboration style. This on-site will be paid.

Step 5: Offer & Reference Checks

If we see a great fit, you will get an offer, including a competitive compensation package with equity participation. At the same time, we’ll ask you to provide 2–3 references so we can gather additional insights into your strengths and working style.