About
You've ordered dinner through Just Eat Takeaway. You've bought and sold on OLX. You've paid with PayU. Chances are, you've already used a Prosus company today. We are Prosus, a global technology company powering some of the world's leading lifestyle ecommerce businesses. Every day, billions of people across India, Latin America, Europe and beyond use our products and services to buy, sell, pay, connect and discover.
Responsibilities
•Own the multi-year product strategy for the platform that underpins every AI initiative across Prosus.
•Define and sequence the roadmap for agent infrastructure, evaluation frameworks, model deployment pipelines, and the shared capabilities that internal teams — from applied science to application engineering — rely on to build and ship AI products.
•Balance long-term platform investments against the immediate, high-impact needs of teams across the portfolio who are racing to deliver.
•Lead and mentor a team of product managers, instilling product discipline and building the PM talent pipeline that scales with the platform.
•Partner closely with engineering and applied science leadership to shape the technical strategy — making the hard trade-offs between model performance, latency, cost, and reliability that determine what we can promise the business.
•Turn ambiguous, fast-moving business needs into clear requirements, align stakeholders across functions and geographies, and ensure that what we build is not just technically impressive but adopted, trusted, and measurably impactful.
Requirements
•Senior product leader experienced in building platform products for internal teams.
•Deeply technical: able to engage substantively with engineering and applied science teams on model lifecycle, MLOps, evaluation frameworks, and infrastructure trade-offs — as a thought partner, not a bystander.
•Understands agentic architectures, LLM capabilities and limitations, and the operational realities of running AI in production at scale.
•People leader who has managed and mentored product managers and takes pride in their growth.
•Sets strategic direction, coordinates overlapping roadmaps into a coherent plan, creates clarity for the team to operate with autonomy and purpose.
•Thrives in ambiguity; has worked in fast-paced, high-scale environments where priorities shift.
•Strong communicator, able to simplify complex technical concepts for executive leadership and dig into detailed requirements with engineering teams.
•Builds trust across functions and geographies; comfortable both pushing back and building consensus.
•Customer-obsessed, even when customers are internal teams.
•8+ years in product management, with at least 3–5 years in formal people-management roles leading a team of product managers.
•Demonstrated success owning platform-level or infrastructure products used by internal teams — ideally including AI/ML platform capabilities, MLOps tooling, or developer-facing services.
•Hands-on experience with generative AI, LLMs, and the model lifecycle (training, fine-tuning, evaluation, deployment, and monitoring) in production environments.
•Track record of defining and executing multi-year product strategies in fast-moving, high-scale environments.
•Ability to engage substantively with engineering and applied science teams on architectural decisions, infrastructure trade-offs, and AI system design.
•Familiarity with agentic workflows, agent frameworks, and operational patterns that make AI agents reliable at scale.
•Strong data-driven decision-making: comfortable with analytics tooling, A/B testing, defining and tracking KPIs, and using metrics to measure adoption, accuracy, latency, and ROI.
•Experience with modern product and engineering tooling (e.g., Databricks, Jira, Confluence, Figma) and agile methodologies.
•Proven ability to mentor and grow product managers, instilling PM best practices and building talent pipelines.
•Stakeholder management across functions and geographies — aligning engineering, applied science, business teams, and executive leadership around a shared roadmap.
•A bias toward ownership: takes accountability for outcomes, protects engineers' focus, course-corrects execution without waiting to be asked.
•Customer-first: translates needs into technical requirements, pushes back when scope dilutes value, advocates relentlessly for the people who use the platform.
•Comfort with ambiguity: structures complex problems, proposes pilots to validate direction, creates clarity for new and evolving teams.
•AI intuition: stays current on models, frameworks, and evaluation methods with the hands-on curiosity of a builder.
Conditions
Own the impact. Work the ecosystem. Earn your growth. Build with backing.
