Veriff

General Counsel

• Serving as the legal point of contact for designated Product Areas, providing actionable advice on legal and privacy risks, compliance strategies, and supplier engagements.
• Executing privacy-by-design initiatives, ensuring compliance throughout the product lifecycle, and drafting the necessary legal documentation.
• Managing and owning data privacy compliance workflows, including the creation and review of DPAs, DPIAs, LIAs, privacy policies, and public-facing privacy notices.
• Supporting privacy negotiations with customers and suppliers, ensuring Veriff’s interests and obligations are clearly represented.
• Monitoring and analyzing emerging legislation, policies, and legal frameworks (e.g., AI laws) relevant to Veriff’s business.
• Advising on global privacy developments and their impact on our product roadmap and international operations.
• Creating and delivering training materials, guidelines, and internal policies to foster a culture of privacy and compliance.
• Collaborating with outside counsel on specialized jurisdictional or technical legal matters.

Senior Privacy and Product Legal Counsel

• Draft, review, and negotiate a variety of commercial agreements to support customer sales, our purchase of software and services from suppliers, and growth-driven partnerships with both startups and public companies. Your primary focus will be on our service subscription agreements, software licenses, data processing agreements, and NDAs.
• Advise on a variety of areas ranging from intellectual property, data privacy, data security, software licensing agreements, and go-to-market strategy from a legal point of view.
• Provide input on processes and policies to help scale the organization, and make our team more effective and efficient.
• Stay up-to-date on relevant industry, commercial, open source, IP, AI, privacy, employment, and other laws, regulations, and developments to be able to give the most effective advice.
• Develop the company’s knowledge in areas of special interest, including intellectual property, data protection, AML/KYC, and other regulatory matters.
• Operate independently, and provide practical, decisive guidance to our business teams that balances business objectives with legal risk, taking into account our company policies and negotiation positions.

Senior Commercial Counsel

Operations

• Measure success through strong quality outcomes, reduced risk, and the organisation’s ability to scale without compromising trust or accuracy.
• Own the quality strategy and governance for your area, setting direction, success measures.
• Provide strong leadership, ensuring clear ownership, strong performance, and effective collaboration within the team.
• Work closely with senior stakeholders to translate quality needs into clear decisions and improvements, aligning standards, tooling, and ways of working so quality remains a core enabler of both customer satisfaction and product excellence.
• Build and evolve quality operations that supports accurate, reliable, and scalable identity verification.
• Guide quality strategy and governance across products and operations by providing data-driven insight and recommendations.
• Translate quality needs into clear priorities, decisions, and requirements.
• Work closely with Product, Go To Market, Operations, and other stakeholders to manage quality impact and risk.
• Use data and quality insights to identify trends, reduce risk, and drive continuous improvement.
• Ensure processes and tooling keep pace with growing complexity and scale.
• Communicate clearly with senior stakeholders and partners, managing expectations and aligning on priorities.
• Lead and support a quality operations team to deliver strong outcomes and sustainable performance.

Area Lead – Quality Operations

Engineering Manager

• Leading, growing, and developing a high-performing team of data scientists and ML engineers responsible for face biometrics and liveness detection models
• Defining the team's structure and evolution as it scales, introducing strong research-to-production practices, clear ownership, and measurable outcomes
• Owning the end-to-end delivery of biometric ML systems — from data strategy and model training to evaluation, deployment, monitoring, and iteration in production
• Driving the development of state-of-the-art face recognition, face liveness, and anti-spoofing models, with a strong focus on robustness, generalization, and fairness across geographies and demographics
• Partnering closely with Product, Authentication, Identity, and Fraud teams to translate verification, authentication, and fraud prevention problems into well-defined ML objectives, metrics, and roadmaps
• Working with ML Platform teams to ensure efficient training pipelines, scalable inference, strong observability, and continuous monitoring of model performance and drift
• Ensuring regulatory compliance, data privacy, and responsible AI practices are embedded into how models are designed, trained, and evaluated
• Building a team culture centered on scientific rigor, experimentation, collaboration, and high-quality execution
• Contributing to Veriff's long-term biometric strategy by anticipating and defending against emerging threats such as deepfakes, replay attacks, and generative AI–based fraud
• Mentoring senior data scientists and ML engineers, supporting their technical growth and leadership development

Machine Learning Engineering Manager – Face Intelligence

Full-stack Engineer

• Build & Scale: Design high-performance, maintainable, and secure systems that handle millions of verifications.
• Lead & Mentor: Set the bar for technical excellence, sharing knowledge and guiding engineers.
• Innovate & Optimize: Improve automation, scalability, and reliability.
• Own & Deliver: Take responsibility for end-to-end development in collaboration with product and design.
• Solve with a Holistic Mindset: Apply curiosity, adaptability, and multi-skill problem-solving to technical challenges.

Senior Software Engineer – Product Platform

• Leading, growing, and developing a high-performing team of data scientists and ML engineers responsible for face biometrics and liveness detection models.
• Defining the team's structure and evolution as it scales, introducing strong research-to-production practices, clear ownership, and measurable outcomes.
• Owning the end-to-end delivery of biometric ML systems — from data strategy and model training to evaluation, deployment, monitoring, and iteration in production.
• Driving the development of state-of-the-art face recognition, face liveness, and anti-spoofing models, with a strong focus on robustness, generalization, and fairness across geographies and demographics.
• Partnering closely with Product, Authentication, Identity, and Fraud teams to translate verification, authentication, and fraud prevention problems into well-defined ML objectives, metrics, and roadmaps.
• Working with ML Platform teams to ensure efficient training pipelines, scalable inference, strong observability, and continuous monitoring of model performance and drift.
• Ensuring regulatory compliance, data privacy, and responsible AI practices are embedded into how models are designed, trained, and evaluated.
• Building a team culture centered on scientific rigor, experimentation, collaboration, and high-quality execution.
• Contributing to Veriff's long-term biometric strategy by anticipating and defending against emerging threats such as deepfakes, replay attacks, and generative AI–based fraud.
• Mentoring senior data scientists and ML engineers, supporting their technical growth and leadership development.

Engineering Manager, Face Intelligence

• Partner with Marketing Ops on campaign setup and tracking structure, and ensure tooling across marketing systems is equipped to support campaigns
• Manage campaign intake, planning support, and execution readiness
• Ensure leads and buying signals are handled correctly and routed appropriately
• Execute and coordinate cross-functional, one-off campaign email sends
• Build and maintain campaign dashboards and reporting that surface performance, pipeline impact, and engagement trends
• Partner with Campaign and Lifecycle colleagues to support campaign planning, building, and orchestration
• Improve processes, documentation, and repeatability as the campaign engine scales