Senior AI Engineer

Job description

Bally’s Intralot is a newly formed company established through the combination of Intralot and Bally’s International Interactive, positioning the group as a top iGaming operator and a leading global provider of lottery solutions. Bally’s Intralot is uniquely positioned across digital online gaming markets, lottery, iLottery, and sports betting. Operating at the intersection of technology, regulation, and entertainment. We are optimally positioned to capitalise on strong global growth trends driven by digital adoption and regulatory expansion across lottery and iGaming markets. Well, what about the team? Join our AI Transformation team to create new capabilities and rethink how teams across Product and Technology work. Our programme aims to help teams ship faster, improve quality, reduce the effort and cost of delivery, build products that strengthen our competitive position, and develop our people’s skills. We turn promising ideas into working products and practices that teams can adopt and reuse across the business. As a Senior AI Engineer, you will be empowered to identify opportunities, propose ideas and build new products, tools and ways of working. You will take ownership of your own initiatives, from a clear hypothesis and agreed success measures through experimentation, production delivery and learning. Alongside this, you will work with engineering teams to turn their prototypes into reliable production products, own shared transformation tooling, and showcase new approaches through demos, tech talks, workshops and pairing. This role combines the creativity to see what could be different with the engineering judgement and drive to make it happen. So, what will you be doing? Originate and build new capabilities: Proactively identify opportunities across Product and Technology, turn them into practical proposals, and build products, internal tools, automations and agents that create value. Own selected initiatives from discovery through delivery, working with stakeholders to connect each idea to a clear programme outcome. Run experiments that lead to decisions: State the opportunity and hypothesis, then agree the success measure and threshold before building. Create the smallest useful experiment, use a feature flag or controlled rollout where appropriate, and measure against a control or baseline at an agreed review date. Use the evidence to scale, c…