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About the Role
Refractal is building the data foundation for an AI security company, including an evidence store for auditors, analytics for compliance reporting, and datasets for model training.
Responsibilities
- Design the data model for an append-only, cryptographically signed evidence store.
- Build the streaming and batch layer to process ingested activity and detections into queryable data.
- Own data quality, retention, residency, and deletion controls for regulated customers.
- Build training and evaluation datasets in collaboration with data scientists and security engineers.
- Enable quick compliance reporting against the EU AI Act, NIST AI RMF, and ISO/IEC 42001.
Requirements
- 6+ years in data engineering, owning production pipelines.
- Strong Python and SQL skills.
- Experience with Postgres and a data warehouse or analytics store (e.g., BigQuery, ClickHouse).
- Experience with streaming technologies (e.g., Kafka, Pub/Sub).
- Experience with orchestration tools (e.g., Airflow, Dagster).
- Data modeling for audit trails, lineage, and multi-tenant isolation.
- Security-minded handling of sensitive data.
- Experience with data work in banking, insurance, or other regulated industries (nice to have).
- Experience with UK GDPR and data residency (nice to have).
Skills
- Python
- SQL
- Postgres
- BigQuery
- ClickHouse
- Kafka
- Pub/Sub
- Airflow
- Dagster
Location
- Remote
Work Type
- Full-time
Experience Level
- 6+ years
Salary/Compensations
- £80,000–£135,000
Benefits
- Competitive equity
- Pension contribution
- Private medical cover
- Private dental cover
- Visa support
- Relocation support
About the Company
- Refractal is an AI security company building infrastructure to defend against autonomous AI threats.
- Founded with expertise from MIT, Microsoft, NASA, and the U.S. Navy.
- Product detects AI-enabled threats at low cost without sacrificing detection quality.
- Combines proven cybersecurity methods with frontier AI security research.
- Works with governments and organizations that cannot afford security failures.
- Backed by leading deep-tech and cybersecurity investors.
- Values: Radical transparency, public service, fail fast, pragmatism over dogmatism.