Provenya is building the trust infrastructure that helps organisations scale AI, data sharing, and digital asset ecosystems with confidence. We work at the intersection of applied R&D, governance engineering, and commercial delivery—turning complex requirements into practical systems that stand up to procurement, regulation, and audit.
What we value: rigor without bureaucracy, clarity over jargon, and research that ships—validated, documented, and ready for real-world adoption.
Why Work With Us
- High-impact problems — provenance, compliance evidence, and rights clarity are now critical barriers to AI adoption
- Research meets delivery — we build methods and tooling that are used in live programmes and real deployments
- Cross-sector exposure — healthcare, public sector, infrastructure, climate, manufacturing, and digital content ecosystems
- Professional growth — a culture of mentorship, documentation, peer review, and continuous learning
Our R&D Practices
Provenya’s R&D is guided by the principle that trust is measurable. We adopt the highest standards of responsible research and innovation, focusing on reproducibility, transparency, security, and ethical integrity—while staying commercially grounded.
Research Integrity & Reproducibility
- Clear hypotheses and evaluation plans for research tasks, with measurable success criteria
- Reproducible workflows using version control, structured experiment tracking, and documented environments
- Peer review as standard for research outputs, code, and technical documentation
- Traceable decisions through design logs and rationale capture—especially where trade-offs impact risk
Data Governance, Privacy & Security by Design
- Data minimisation and purpose limitation as default engineering constraints
- Secure development practices including access control, secrets management, and dependency hygiene
- Lifecycle governance for datasets and models: sourcing, consent/rights, transformation, retention, and deletion
- Audit-ready documentation to support internal review, procurement, and regulatory scrutiny
Responsible AI & Assurance
- Risk-based approach to system design, aligned to operational context and intended use
- Bias and performance assessment with domain-relevant metrics and clear reporting of limitations
- Monitoring and change control for deployed models, including drift and incident response pathways
- Evidence packs that connect requirements to controls, tests, and outcomes
Open, Collaborative, and Commercially Relevant Research
- Documentation-first culture to enable collaboration across partners and disciplines
- Interoperability by default using open standards where appropriate and clear interface contracts
- From prototypes to products — validation, scalability planning, and adoption pathways are considered early
- Responsible IP and licensing to ensure outputs can be exploited, shared, or transferred with clarity
What We Look For
We hire people who combine strong technical depth with high standards of professional practice. You may be a fit if you care about shipping trustworthy systems and can communicate clearly with both technical and non-technical stakeholders.
- Applied researchers and engineers (AI/ML, data engineering, software engineering)
- Governance and assurance specialists (AI assurance, risk, compliance evidence, quality)
- Digital rights and provenance practitioners (IP, licensing, traceability, metadata)
- Programme delivery roles (innovation delivery, pilots, stakeholder coordination)
How to Apply
We share roles as they open. If you do not see a listed position, you can still submit an expression of interest. We are particularly keen to hear from candidates with a track record of rigorous delivery and strong documentation practices.
- Send your CV and a short note on the type of role you are seeking
- Include links to relevant work (publications, GitHub, portfolio, reports, or case studies)
- Highlight one example where you improved quality, traceability, or assurance in a project
Note: Provenya is committed to fair, inclusive hiring. We welcome applicants from diverse backgrounds and value evidence of capability, curiosity, and professional integrity.