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Posted 6 days agoAI Risk & Technical Governance Specialist
at Superapp
SpainOn-site
Responsibilities
- Review AI and ML systems at a technical level, including model design, feature pipelines, training approaches, validation methods, deployment architecture, monitoring controls, and human oversight mechanisms.
- Design and maintain practical governance artefacts such as AI inventories, use-case classification approaches, risk assessment templates, control libraries, testing standards, and review rubrics.
- Perform technical governance reviews and audits of AI systems and supporting processes.
- Test the design and operating effectiveness of AI-related controls and identify remediation actions where gaps exist.
- Produce structured findings, risk opinions, and assurance reports for technical and non-technical stakeholders.
- Support audit and regulatory readiness by building defensible compliance narratives and evidence packs.
- Develop dashboards and reporting views that provide visibility of AI use cases, risk status, control coverage, review outcomes, incidents, and remediation progress.
- Oversee or challenge post-deployment monitoring for model performance, fairness, stability, drift, and adverse customer or business outcomes. _*]:min-w-0 gap-3">
- Build organisational capability by translating regulatory and governance expectations into practical guidance, playbooks, and training.
Requirements
- As AI Risk & Technical Governance Specialist at Super Technologies, you will sit at the intersection of AI/ML technical expertise and governance, risk, and regulatory compliance.
- Working across product, engineering, data science, and risk teams, you will operationalise AI governance across the full model lifecycle — ensuring our AI systems are trustworthy, compliant, and built to withstand regulatory scrutiny.
- This is a hands-on role that requires both deep technical fluency and the ability to translate complex AI concepts into clear governance and risk positions. _*]:min-w-0 gap-3">
- Technical AI governance and assurance _*]:min-w-0 gap-3">
- Operationalise AI governance
- requirements across the full AI lifecycle, from ideation and use-case approval through development, validation, deployment, monitoring, change management, and retirement.
- requirements under the EU AI Act, GDPR, LGPD, and other relevant frameworks.
- Assess whether AI systems have the right documentation, controls, and evidence to support internal governance, regulatory scrutiny, and audit. _*]:min-w-0 gap-3">
- requirements for AI systems, including documentation of intended purpose, system design, data lineage, validation, performance metrics, limitations, human oversight, and post-deployment monitoring. _*]:min-w-0 gap-3">
- Help define and track meaningful AI governance, risk, and assurance metrics.
- Work directly with data scientists, ML engineers, product teams, and business owners to help them build compliant and trustworthy AI systems without slowing innovation unnecessarily.
- Keep stakeholders informed on emerging AI regulatory developments, assurance techniques, and good practice. _*]:min-w-0 gap-3">
- experience across AI/ML, model risk, technical assurance, or technical AI governance, with a meaningful part of that
- experience in a regulated environment.
- Prior background as an ML engineer, data scientist, model validator, AI architect, or similar technical role, with subsequent
- experience in AI governance, AI assurance, model risk, or regulatory delivery. •
- Experience conducting deep reviews of AI/ML systems beyond policy conformance, including assessment of model design, validation, monitoring, and operational controls. •
- Experience translating technical AI concepts into regulatory, risk, audit, or compliance language for senior stakeholders. •
- Experience implementing governance processes, controls, and assurance mechanisms in real delivery environments, not just designing high-level frameworks.
- Strong working knowledge of several of the following: EU AI Act, GDPR/LGPD and automated decision-making considerations, ISO/IEC 42001, ISO/IEC 23894, NIST AI RMF, OECD or other leading responsible AI frameworks, and sector expectations relevant to gambling, customer protection, and technology risk.
- Strong understanding of how AI and ML systems are built, evaluated, deployed, and monitored in production.
- Familiarity with common ML approaches, LLM/generative AI patterns, model lifecycle tooling, and data/ML platforms.
- Familiarity with cloud-based AI environments such as AWS, Azure, or GCP.
- Strong written skills, including the ability to produce clear review reports, risk assessments, control evaluations, and executive-ready summaries.
Benefits
- Medical / Health Insurance Open Annual Leave
- Everything we do at Super is rooted in doing what is right: for customers, for each other, and for our long-term vision.
Additional details
- We are on a mission to pioneer the world’s next era of play.
- As we grow across Europe and Latin America, we’re building The Playstack - the technology powering the next generation of sports, gaming, and fan experiences.
- Join us, and help make it the most widely used platform in the world! From operations, to marketing, to product, we are looking for talented people who will shape how millions of customers play, watch, and connect every day. _*]:min-w-0 gap-3">
- Translate technical system characteristics into clear governance, risk, and regulatory positions, including mapping to
- Embed governance checkpoints, review criteria, and control
- requirements into product, engineering, and model development workflows.
- Audit, compliance, and regulatory readiness _*]:min-w-0 gap-3">
- Escalate material issues, control weaknesses, or ethical concerns and track remediation through to closure. _*]:min-w-0 gap-3">
- Business partnership and capability building _*]:min-w-0 gap-3">
- What we are looking for _*]:min-w-0 gap-3"> Extensive