Product Manager
Cerberus Capital Management · London Area, United Kingdom
Apply & track with Apply EdgeFounded in 1992, Cerberus is a global leader in alternative investing with approximately $71 billion in assets across complementary credit, private equity, and real estate strategies. We invest across the capital structure where our integrated investment platforms and proprietary operating capabilities create an edge to improve performance and drive long-term value. Our tenured teams have experience working collaboratively across asset classes, sectors, and geographies to seek strong risk-adjusted returns for our investors. For more information about our people and platforms, visit us at www.cerberus.com.Cerberus Technology Solutions (CTS)We are a new, but growing team of AI specialists - software engineers focused on AI development, and technology strategists - working to transform how an alternative investment firm with $71B in assets under management leverages technology and data.Our remit is broad, spanning investment operations, portfolio companies, and internal systems, giving the team the opportunity to shape the way the firm approaches analytics, automation, and decision-making.We operate with the creativity and agility of a small team, tackling diverse, high-impact challenges across the firm. While we are embedded within a global investment platform, we maintain a collaborative, innovative culture where our AI talent can experiment, learn, and have real influence on business outcomes.Responsibilities:Own product strategy, backlogs and roadmaps, assessing technology gaps, market opportunities and readiness for deployment against strategic priorities.Define and communicate a clear product vision, translating customer needs, market trends and business objectives into actionable plans for engineering and deployment teams.Conduct customer, market and competitor research to identify opportunities for differentiated AI products and prioritize investments based on customer value and business impact.Strength in user engagement, creating communication channels and resources enabling adoption and gathering of feedback. Also, provision of training sessions and materials as appropriate.Understanding of design principles and UX, enabling the engineering team to build experiences of high value. Taking UX from ideation to customer-facing live deployments.Establishing a heartbeat with engineering, keeping them active and engaged, reviewing upcoming build requirements and assessing adequate resourcing for feature buildsQualifications:7-12 years technical experience and well-demonstrated expertise on a wide range of AI and ML topics, having successfully deployed AI applications to 100s of users. With full confidence in each aspect of the software development lifecycle.Active and sustained interest in building software products with AI, to transform existing business in Financial Services.Interpersonal skills and ability to lead internal and external workshops, scoping sessions and deal with ambiguity. With stakeholders looking to you to prioritize, in live sessions and via materials shared.Strong stakeholder management skills, ability to speak at high and granular levels on complex, inter-related technology concepts, and articulate why a product wins, its differentiators and the business value it creates. Ability to motivate and lead the business, explaining unlocked business value from abstract technical concepts.Ability to coordinate between various teams with their own roadmaps, and work with these teams to integrate efforts and drive adoption.Ability to motivate a team of busy engineers, with competing priorities. Providing coaching and clarity on focus areas, both current and upcoming. Promoting product management best practice.Experience in running agile teams, delivering against tight deadlines and sponsoring the build of reusable, modular components. Willingness to implement and drive ceremonies, meetings and standups commensurate with the engagement required to deploy quickly.Experience and willingness to own QA and UAT processes as product or new features go live. Including ownership of go/no-go decision boundaries and enforcing them.