heyData is building a compliance platform that guides companies — from 10-person startups to 400-person multi-entity organisations — step by step to audit-ready outcomes across ISO 27001, NIS2, GDPR, and more. Compliance is fundamentally a knowledge and process problem, and AI is one of the most powerful tools we have to solve it.
We're hiring our first Senior AI Engineer: the person who will identify where AI can eliminate manual work, build the systems that make it happen, and own those systems end-to-end. You'll work directly with Product, Engineering, and our compliance experts to discover real problems and ship real solutions.
This is a builder role. You'll spend most of your time shipping AI-powered features that customers and internal teams can actually use — so you need to make infrastructure decisions that are pragmatic today and extensible tomorrow.
The role is fully remote, with a focus on Germany and Serbia.
Work directly with Product, the VP of Engineering, the Engineering Team Lead, and compliance experts to understand pain points and manual workflows that AI can automate.
Translate fuzzy problem descriptions into clear AI feature specs: what the system does, what data it needs, how success is measured.
Push back confidently when AI is not the right solution — and propose alternatives.
Design and implement AI features using foundation models (OpenAI, Anthropic, Mistral) as a starting point, customised with RAG pipelines, prompt engineering, and fine-tuning where justified.
Expose your AI services as clean RESTful APIs consumed by the rest of the application (NestJS/VueJS stack on AWS EKS).
Build data ingestion and transformation pipelines to feed AI systems with heyData 's internal data and customer data, handled with strict GDPR compliance.
Integrate AI agents and multi-step workflows where appropriate, using frameworks like LangChain or LlamaIndex pragmatically.
Manage the full lifecycle of every AI system you build: development, deployment, monitoring, and retraining.
Set up CI/CD pipelines for AI models integrated into our existing AWS infrastructure.
Monitor model quality in production — detect drift, evaluate output quality, and trigger retraining when needed.
Document your systems clearly so the team can understand, operate, and extend them.
Design and run AI/ML experiments rigorously: clear hypotheses, appropriate evaluation metrics, statistically sound interpretation.
Communicate findings to non-technical stakeholders in plain language. Help the team make decisions based on evidence, not intuition.
Stay current with the rapidly evolving AI landscape (model providers, tooling, evaluation frameworks) and bring relevant developments to the team.
5+ years total software engineering experience, with at least 3 years specifically building and operating production AI/ML systems.
Proven track record shipping LLM-powe