LOGEX

AI Engineer

Hamburg, Germany full-time Mid Salary not listed
full-time Mid level Technology & IT Curated
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About the role

Our mission
Better healthcare outcomes depend on turning data into intelligence that can be trusted and acted on. LOGEX holds financial, operational, clinical and pathway data for healthcare providers across Europe, and AI is becoming central to how we turn that data into value — in our products and in how we work. We are building that capability deliberately, with the rigour a regulated healthcare-data business demands.
This is a hands-on building role — you will help shape LOGEX’s AI journey and deliver AI capabilities into our products, with the teams.

The role
As AI Engineer, you will help shape and deliver LOGEX’s AI journey — building applied AI capabilities into our products and, where useful, into how we work. You will turn AI use cases into working, reliable software: integrating LLMs and applied AI, building pipelines, and applying machine learning where it fits the problem. The emphasis is on delivering dependable, in-product AI capabilities with the teams, and making sure what you ship is tested, monitored and dependable enough for healthcare data.
You will work closely with the AI Architect, data engineers, platform and product teams, and play a central part in turning the AI direction into real features customers use — moving capabilities from prototype to production.

What you will own
In-product AI capabilities. Design, build and ship AI capabilities into LOGEX’s products with the teams — from idea through to integrated, working features that customers use.
LLM and applied AI development. Build with modern AI approaches — LLM integration, retrieval-augmented generation, prompt and evaluation design — and apply machine learning where it fits the problem.
Production reliability (MLOps / LLMOps). Make AI dependable in production — deployment, monitoring, evaluation, versioning and continuous improvement of the capabilities you build.
Quality, safety and compliance. Build AI that is tested, evaluated, secure and privacy-preserving, appropriate to a regulated healthcare-data environment.

Your impact and responsibilities
•      Build and ship in-product AI capabilities with the product and engineering teams
•      Integrate LLMs and applied AI — RAG, prompting, evaluation — into real product features
•      Help turn LOGEX’s AI direction into working, reliable software
•      Build evaluation, testing and monitoring into AI capabilities so they are reliable and observable
•      Deploy and operate AI in production (MLOps / LLMOps), and improve it over time
•      Prepare and work with data for AI, in partnership with data engineering
•      Apply machine learning where it fits the problem, alongside LLM-based and applied-AI approaches
•      Write clean, well-tested code and take part in code reviews
•      Build AI capabilities that are secure, privacy-preserving and compliant (GDPR and similar)
•      Work with the AI Architect to follow shared patterns, standards and guardrails
•      Apply AI to internal engineering, QA and operational workflows where it adds value

Your profile
We are looking for a hands-on AI engineer who can build reliable AI capabilities and bring them into production.
Experience
•      Solid experience building AI capabilities and shipping them into products or production
•      Experience integrating modern AI (LLMs, RAG) into real applications
•      A strong software / data engineering background, with hands-on AI delivery
•      Experience with building and deploying ML models is relevant and valued, though not the primary focus
•      Experience working in regulated environments (healthcare, financial services or similar) is an advantage

Technical depth
•      Strong coding ability (for example Python) and solid software engineering fundamentals
•      Hands-on experience with LLM-based and applied-AI development — frameworks, cloud AI services and orchestration
•      Practical experience with RAG, prompting and evaluation, and with integrating AI into real products
•      Working knowledge of MLOps / LLMOps — deployment, monitoring, evaluation and versioning
•      Good data engineering skills — preparing and working with data for AI
•      Working knowledge of machine learning — training, tuning and serving models — where it fits the problem
•      Awareness of AI safety, privacy and responsible-AI practice

Delivery and execution
•      Strongly outcome-driven — measured by reliable AI capabilities shipped into production, not prototypes
•      Hands-on and pragmatic, with strong attention to quality, evaluation and reliability
•      Comfortable working where AI approaches and ways of working are still forming

Personal style
•      Collaborative and a strong communicator, equally effective with engineers and data practitioners
•      Pragmatic about AI — focused on real value and reliability over hype
•      High standards, but pragmatic; comfortable operating with pace and ambiguity
•      Willing to travel moderately across LOGEX’s locations

Why LOGEX?
25 vacation days (based on full-time employment) to recharge, with the option to purchase additional days

An informal working environment with motivated colleagues

The possibility to work in a hybrid setup

A laptop and everything you need to set up a comfortable and ergonomic home office

Personal and professional development opportunities through our LOGEX Academy

Access to our mental health partner, OpenUp

Regular after-work drinks and many more social events

Contact us!
You can apply via the button below and upload your CV. For more information, or in case you have any
questions, you can contact Wesley Schreuder at

Interview prep

Walk in with sharper answers.

Use this as a quick practice sheet before you speak with the employer.

Mid
Technology & IT API integration Figma Python Engineer Technology Mid level

Likely questions

  1. Tell us about work you have done that is close to the AI Engineer role.
  2. How would you approach your first 30 days at LOGEX?
  3. Which of API integration, Figma and Python have you used recently, and what did it help you achieve?
  4. Describe a time you solved a problem without waiting to be told exactly what to do.
  5. How do you handle busy days, changing priorities, or pressure at work?

Prepare before the call

  • A recent example that proves your experience with API integration, Figma and Python.
  • One short story with a problem, your action, and the result.
  • Two examples that show the strengths listed on your CV.
  • A clear reason why this role and company interest you.
  • Your availability, preferred work style, and salary expectations.

Ask them

  • What would success look like in the first 90 days?
  • What are the main problems this hire should help solve?
  • How does the team give feedback and measure good work?
  • What does a normal working week look like for this role?
Practice line

I am interested in the AI Engineer role because I can bring practical experience in API integration, Figma and Python, learn the team quickly, and contribute to the outcomes LOGEX needs from this hire.

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