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About the role
You will design and build the data foundation, including an append-only evidence store and streaming/batch pipelines for analytics and compliance. You will also collaborate with data scientists to create training datasets and ensure data quality and security for regulated customers.
What they look for
Requirements
The role requires 6+ years of experience in data engineering with strong proficiency in Python, SQL, and modern data warehouse technologies. Candidates must have experience with streaming and orchestration tools, as well as a security-minded approach to handling sensitive data.
Benefits
Full description
About Refractal
Refractal is an AI security company building the infrastructure organisations need to defend against autonomous AI threats. 2026 has shown that generally capable intelligence is here. The challenge now is modernising security to stop AI-enabled threats, whether they come from internal agents going rogue or from attackers using AI to become more dangerous.
Refractal was founded on cybersecurity and AI expertise from MIT, Microsoft, NASA and the U.S. Navy. Our product lets organisations detect AI-enabled threats at low cost without sacrificing detection quality. We take a practical approach to AI risk, combining proven cybersecurity methods with frontier AI security research.
Today, we work with governments and organisations that can't afford to get security wrong. We're backed by leading deep-tech and cybersecurity investors and are growing the team to deliver on this mission.
The role
You'll build Refractal's data foundation, including the evidence store that customers' auditors rely on, the analytics behind compliance reporting and the datasets our models are trained on.
What you'll do
- Design the data model for our append-only, cryptographically signed evidence store.
- Build the streaming and batch layer that turns ingested activity and detections into queryable data.
- Own data quality, retention, residency and deletion controls for regulated customers.
- Build training and evaluation datasets with our data scientists and security researchers.
- Make compliance reporting against the EU AI Act, NIST AI RMF and ISO/IEC 42001 quick to produce from our data.
Success in your first six months
- The evidence store is in production, documented and trusted by customers' auditors.
- Colleagues answer compliance and detection questions from data you own, without ad hoc work.
- Training and evaluation data has clear provenance and separation.
About you: essential
- 6+ years in data engineering, owning production pipelines.
- Strong Python and SQL, with Postgres plus a warehouse or analytics store such as BigQuery or ClickHouse.
- Experience with streaming (Kafka, Pub/Sub or similar) and orchestration (Airflow, Dagster or similar).
- Data modelling for audit trails, lineage and multi-tenant isolation.
- Security-minded handling of sensitive data.
Nice to have
- Google Cloud experience, or data work in regulated industries.
- Montenegrin, Serbian, Bosnian or Croatian.
Our values
Radical transparency. We believe the best work happens when everyone feels able to give and receive honest, constructive feedback.
Public service. We see AI security as a form of public service. Getting the AI transition right means putting the right infrastructure in place to manage the threats that come with it, and our work helps protect the institutions and services society depends on.
Fail fast. We test ideas early, seek feedback and learn quickly. We experiment rapidly and change course when something isn't working, without compromising on security.
Pragmatism, not dogmatism. We choose approaches based on how well they solve the problem. That means combining established cybersecurity methods with frontier AI research, questioning our assumptions, and changing our minds when the evidence changes.
Compensation and benefits
- Salary: €35,000–€80,000 gross per year
- Competitive equity to share in Refractal's growth
- Pension contribution
- Private medical and dental cover
- Visa and relocation support
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