checkout.com - AI Product & Transformation Lead - Legal & Enterprise Risk
Requirements
• Experience building AI products, automation, digital capabilities or technology-enabled ways of working in a complex organisation. • A track record of taking ambiguous problems from discovery through to a practical outcome that people actually use. • Deep practical experience with generative AI, AI agents, workflow automation, knowledge management, no-code or low-code tools, or similar technologies. • Strong user-centred instincts: you listen carefully, understand how work is really done and design for adoption rather than theoretical capability. • Strong judgement about confidentiality, privilege, data protection, security, accuracy and responsible use of AI. • A coaching mindset and the ability to help others become more confident and capable builders. • Curiosity, pragmatism and a bias towards learning by doing. • It’s important we set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable. • Life at Checkout.com http://Checkout.com • We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection. • Curious about what it’s like to be part of our team? Visit our Careers Page https://www.checkout.com/careers to learn more about our culture, open roles, and what drives us. • For a closer look at daily life at Checkout.com http://Checkout.com, follow us on LinkedIn https://www.linkedin.com/company/checkout/life/ and Instagram https://www.instagram.com/checkout_com/
Responsibilities
• Build and scale AI products: • Lead structured discovery with Legal and Enterprise Risk teams to identify high-value AI opportunities, recurring friction, manual work and decision bottlenecks. • Turn real user problems into clear use cases, lightweight prototypes and scalable solutions. • Build, configure or product-manage AI-enabled tools, agents, workflow automations, self-service experiences and knowledge systems. • Take solutions from idea to pilot to adoption, including testing, iteration, documentation and handover. • Balance speed and experimentation with appropriate controls for confidentiality, privilege, data protection, security and legal risk. • Help others build products: • Make practical AI-building skills accessible to lawyers, risk professionals and Legal Operations colleagues through hands-on sessions, guides and coaching. • Establish an AI builder community or similar forum for sharing use cases, prompts, prototypes, lessons and reusable components across Legal and Enterprise Risk. • Map and redesign workflows across Legal and Enterprise Risk, using AI to improve speed, quality, consistency and capacity. • Create repeatable processes, templates, playbooks and operating rhythms that reduce unnecessary manual effort. • Design better ways to capture, organise, retrieve and reuse organisational knowledge through AI-enabled search, summarisation and assistance. • Identify opportunities to improve intake, triage, matter management, contract workflows, reporting and business self-service. • Establish simple measures of impact, such as time saved, cycle-time reduction, quality improvements, user satisfaction and adoption. • Build alignment and momentum • Own a prioritised AI product and use-case pipeline based on user need, value, feasibility, adoption potential and risk. • Bring stakeholders together around clear problems and decisions rather than abstract technology discussions. • Communicate progress, learnings and trade-offs in a way that works for both technical and non-technical audiences. • Build strong relationships with Technology, Data, Information Security, Procurement and other partners needed to deliver safely at scale. • Help Legal and Enterprise Risk leadership make informed choices about AI tools, investment, capability, governance and ways of working.
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