AI Engineer
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Position Overview & Specifications
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
Candidate Selection & Onboarding Process
Application & Resume Screening
Submit your tailored CV/Resume directly to the talent acquisition portal.
Technical & Competency Interviews
Virtual interviews with the hiring manager and multidisciplinary team.
Formal Offer & Benefits Negotiation
Written agreement outlining compensation, equity, retirement vesting, and relocation allowances.
Onboarding & Corporate Integration
Equipment provisioning, team orientation, and commencement of duties.
United States Work Authorization & Sponsorship Guide
Under United States immigration law (INA § 101(a)(15)(H)), foreign nationals seeking full-time professional positions typically navigate either non-immigrant specialty occupation classifications or immigrant visa sponsorship:
Requires a relevant Bachelor's degree or higher. Employers must file an approved Labor Condition Application (LCA) with the US Department of Labor confirming the prevailing wage rate.
Canadian and Mexican citizens qualify under USMCA (TN status). F-1 STEM graduates benefit from 36-month aggregate work authorization through E-Verify enrolled employers.
Candidate Preparation Blueprint: Technology
Based on transatlantic hiring benchmarks for AI Engineer roles across LOGEX's corporate sector, successful applicants typically excel across three core dimensions:
Demonstrated portfolio evidence, architecture/system design case studies, or validated professional certifications directly applicable to Technology.
STAR method competency responses highlighting cross-functional leadership, conflict resolution, and delivering measurable enterprise ROI under tight timelines.
Total compensation expectation aligned within the benchmarked Salary Disclosed on Application bracket, including retirement vesting and health parity.
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