Senior Product Manager | Applied AI

EPAM Systems, Inc.; Brasil; Teletrabalho; BRL 260 000 - 450 000; Tempo integral

Resumo da oferta

EPAM Systems, Inc. is growing a product-management team that runs AI-powered products and applies AI across the product lifecycle. As a Senior Product Manager | Applied AI, you will own the vision, strategy, roadmap and end-to-end delivery of one or more products — at least one AI-powered.

This is a product role, not an engineering role. You will define AI feature requirements, set evaluation criteria and guardrails, mentor other Product Managers, and collaborate with engineering, data, design

Qualificações

• 5+ years in Product Management, with end-to-end ownership.

Responsabilidades

• Own vision, strategy, roadmap and end-to-end delivery of AI-powered products.

Conhecimentos

Product management

AI literacy

Stakeholder management

Backlog management

Team leadership

Requirements analysis

Cross-functional collaboration

GenAI/LLMs understanding

Prototyping

Roadmapping

Ferramentas

AI builder tools

GenAI platforms

Descrição da oferta de emprego

We are growing a product-management team that runs AI-powered products and applies AI across the whole product lifecycle. As a Senior Product Manager | Applied AI, you will own the vision, strategy, roadmap and delivery of one or more products — at least one of them AI-powered — while using AI day-to-day to work faster and make sharper decisions and mentoring other Product Managers as you do.What \"Applied AI\" means here. This is a product role, not an engineering role. We expect confident, practical command of AI as a product manager — using it across the lifecycle and shaping AI-powered features — not the ability to build, train or tune machine-learning models as an ML engineer or data scientist would.ResponsibilitiesOwn the vision, strategy, roadmap and end-to-end delivery of one or more products, including at least one that is AI-poweredDefine requirements and use cases for AI features, treating them as probabilistic products — scoping data and use-case fit, and setting evaluation criteria, quality bars, guardrails and human-in-the-loop review as acceptance criteriaIdentify where AI can improve the product, the customer experience, internal processes or business outcomes — and build and size the case for itUse AI tools productively and with discipline across discovery, research synthesis, analysis, documentation, user stories, prototyping and planning — verifying outputs before relying on themPrioritise features, own the backlog and manage release cycles, using AI-assisted analysis to support (not replace) your decisionsManage the full product lifecycle, including the added considerations of AI features — model/version changes, quality drift and human oversightWork closely with engineering, data, design and AI/ML teams, translating product intent into requirements they can act on and their constraints into product decisionsSet realistic expectations with clients and stakeholders about what AI can and cannot do, and communicate benefits, limitations and risks in plain languageMentor Product Managers and raise the team's practical AI capability by exampleRequirements5+ years in Product Management, having managed one or more products end to end, including post-launch maintenance and supportLaunched more than one product (or key capability) to market, with at least one experience delivering or materially improving an AI-powered product or feature (e.g. GenAI, ML, recommendations, search or automation)Solid ownership of product strategy, vision and roadmap; market analysis and product visioning — including identifying and justifying where AI adds valueExperience owning backlogs, cross-product dependencies and release cycles, and managing product lifecycle and support modelsFamiliarity with product profitability, competitive positioning and pricing — including the cost, latency and quality trade-offs that shape AI-feature economicsExpertise across multiple (3+) business domains, able to act as a business-domain SMEWorking AI literacy — what current AI (including GenAI/LLMs) can and cannot do reliably, common patterns and typical failure modes — enough to make sound product decisions and hold credible conversations with technical teams. Deep model-building knowledge is not requiredAble to influence stakeholders up to and including VP level, and to lead all critical aspects of a product launchAble to lead a team of Product Owners and/or Product Managers across a product line or family, guiding them through the full lifecycleRaises the team's practical AI proficiency — sharing verified ways of working and coaching on requirements and evaluation criteria for AI featuresPractical, daily use of AI across research, discovery, analysis, documentation, user stories, prototyping and planning — with verification of outputsAbility to identify and justify AI opportunities in products, processes, CX and business outcomesWorking AI literacy — concepts, terminology, capabilities and limitations at PM depthExperience defining requirements and use cases for AI features, including evaluation criteria, quality bars, guardrails and human oversightAbility to evaluate AI outputs for quality, accuracy, risk, limitations and user impactResponsible-AI awareness — privacy, bias, security, transparency and human oversightAbility to work effectively with engineering, data, design and AI/ML teamsAdaptability and continuous learning as AI tools and capabilities evolveNice to haveHands-on prototyping with AI builder tools to near-production fidelityBuilding PM agents / multi-step automations across research, backlog, analytics and commsUnderstanding of AI-feature economics (cost, latency, unit economics) and model lifecycle (drift, versioning, vendor change)Familiarity with AI regulation (e.g., EU AI Act) and relevant sector rulesPrior experience taking an AI-powered product to production at scaleEPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.