Senior Product Manager (R&D – AI Platform Operations)

PLAY, GROW and WIN

To be a part of Virtuos means to be a creator.

At Virtuos, we harness the latest technologies to make games better and more immersive than ever before. That is why we pride ourselves in constantly pushing the boundaries of possibility since our founding in 2004.

Virtuosi is a team of experts – people who have come together to share their mutual passion for making and playing games. People with the same enthusiasm for exploring new ideas and the constant drive to excel in their field. People who believe in earning success through dedication.

At Virtuos, we are at the forefront of gaming, creating exciting new experiences daily. Join us to Play, Grow and Win – together.

ABOUT THE POSITION

• Product Direction and Priorities

  • Own the roadmap for the assigned AI platforms. Set quarterly priorities and a longer-term direction with R&D leadership and product owners.

  • Build clear business cases using user evidence, expected benefits, costs, and risks. Make trade-offs across new capabilities, adoption, reliability, and technical improvements.

  • Decide product priorities within agreed goals and capacity. Resolve competing requests across teams and escalate decisions that need wider funding or policy changes.

  User Needs and Product Discovery

  • Lead interviews, workflow reviews, and data analysis to find the problems that matter most. Test assumptions through pilots before committing to broad delivery.

  • Turn findings into clear requirements, acceptance criteria, and success measures. Distinguish shared platform needs from requests that serve a single team.

  Service Quality and Release Delivery

  • Agree service quality goals and release readiness criteria with engineering. Prioritise improvements based on user impact, reliability, and cost.

  • Lead product planning from requirements through rollout. Align dependencies, manage scope, and resolve blockers with engineering and product owners.

  • Coordinate business communication during service issues and ensure follow-up work addresses recurring problems. Engineering retains ownership of technical incident response and recovery.

  Adoption and Business Value

• • Own adoption plans with business teams. Set up pilots, onboarding, documentation, training, and local champions that help users build AI tools into daily work.

  • Define and review measures such as repeat use, task success, time saved, user satisfaction, service reliability, and cost per successful task. Set baselines and agreed targets before rollout.

  • Use results to decide which capabilities to expand, improve, consolidate, or retire. Present progress, costs, risks, and recommendations to R&D and business leaders.

  Responsible AI and Product Leadership

  • Work with engineering, security, legal, and business owners to define requirements for data access, confidentiality, intellectual property, output quality, and human review.

  • Include relevant AI quality checks and approval requirements in pilots and releases. Make limitations clear to users and track issues after launch.

  • Mentor less experienced product colleagues. Improve shared practices for discovery, prioritisation, release reviews, and measuring business value.

• Required Qualifications

• • Typically 6 or more years of relevant experience, including substantial product management ownership of software, SaaS, or internal platforms. Equivalent experience with clear evidence of senior-level responsibility is welcome.

• • A record of independently owning a roadmap and delivering measurable improvements in adoption, user outcomes, service quality, or operating cost.

• • Experience leading discovery, making priority decisions, and taking products or major capabilities from requirements through launch and ongoing improvement.

• • Strong analytical judgement. Able to define useful measures, assess costs and benefits, and use evidence to change course.

• • Experience aligning technical teams and business stakeholders with competing needs. Able to explain difficult trade-offs clearly and influence without direct authority.

• • Working knowledge of AI platform concepts, APIs, usage data, and cloud service costs. Able to discuss AI quality, limitations, and data handling with specialists.

• • Clear written and verbal communication, with experience guiding adoption and change across teams.

• Preferred Qualifications

• • Experience managing AI, machine learning, workflow automation, or internal enterprise products across multiple teams or studios.

• • Experience evaluating AI output quality, setting service targets, or managing usage-based platform costs.

• • Experience in game development, game art, production, or creative technology.

• • Practical experience with Agile delivery, Jira or Azure DevOps, and product analytics tools.