How do you turn a quarter-end close that still runs on spreadsheets into something an agent handles overnight? Help a contact center answer faster and better without adding headcount? Turn a 200-page regulatory change into a plain-English checklist that a compliance team can act on by Monday morning? Get an AI system to read a backlog of contracts and surface only what actually matters?
That’s the work. EPAM’s Applied AI exists to put frontier AI to work inside real businesses - sitting with clients, from the CTO to the people doing the actual job, and turning ambitious, often fuzzy goals into AI solutions that ship and create real value. The work runs from helping a workforce use AI well, to rebuilding a whole process around agents, to launching brand-new AI-native products. We’re looking for an Applied AI Product Manager (Forward Deployed) to own that journey - from the first messy conversation to a live system that earns or saves real money. It’s hands-on and client-facing: you’re the client’s main point of contact, you decide what gets built and why, you run delivery through to a working system, and you prototype solutions yourself rather than handing every idea off. You hold the why and the what; engineering, data and architecture build alongside you for production scale.
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 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
Nice to have
- Pre-sales and solution-shaping experience with senior client stakeholders