Applied AI Product Manager (Forward Deployed)

EPAM Systems is focused on applying frontier AI solutions in real business contexts. They are seeking an Applied AI Product Manager to manage client relationships and lead the development of AI solutions from concept to delivery.

Responsibilities:

• Build, don’t just brief. Prototype working AI solutions and demos yourself, with modern tooling, to prove the idea in pre-sales and get to value fast
• Own the client relationship. Be the day-to-day partner and point of contact, earning trust across the organization and staying straight about trade-offs
• Shape what we build and why. Turn vague, high-stakes goals into a sharp problem statement, a solution, and a definition of success everyone signs up to
• Carry it through. Lead the shaping in pre-sales as a full member of the team, then stay on into delivery so nothing is lost in the handover
• Run the room. Facilitate workshops with business and technical stakeholders, and bring the clarity when the brief is fuzzy or the client changes direction
• Make the case. Build the business case and the ROI story so clients can invest with confidence
• Drive adoption. Work on rollout and change so what you build actually gets used - then feed the lessons back into how we work

Requirements:

• You build with AI, hands-on. You actively prototype with the current toolset - Claude and Claude Code, ChatGPT and Gemini, Cursor, app builders like v0, Lovable or Replit, and agent platforms such as Microsoft Copilot Studio - and you reach for them in your own work by default
• You've delivered AI into production. A track record of taking AI agents or AI-native features all the way into live client use - things that shipped and got used, not prototypes that stayed in the lab
• Customer-facing, high-stakes experience. You've led work where stakeholders weren't aligned, and the path wasn't obvious. Roughly 5+ years in product, consulting - though your track record matters to us more than years or titles
• Deep in one vertical. Real domain depth in at least one industry - Financial Services, Retail Banking, Insurance, Healthcare & Life Sciences, Retail or Travel & Hospitality - so you speak the client's language, not just the technology's
• A real product and value mindset. You're at home with 0→1 product innovation: building from a blank page, under ambiguity, without a playbook
• GenAI fluency. Working knowledge of LLMs, prompting, RAG, embeddings and vector databases, agents and the Model Context Protocol (MCP) - enough to make good calls, not necessarily to write production code
• You can be heard in the room. You ask sharp questions, structure chaos, and move from whiteboarding with execs to a crisp brief for engineers without losing the thread
• Bias for action. You jump into the gaps - a rough prototype over a weekend, a workshop, a demo at short notice - to keep things moving
• Pre-sales and solution-shaping experience with senior client stakeholders