Applied AI Product Leader - Strategy & Delivery

EPAM Systems; New York (NY); Remote; USD 130,000 - 200,000; Full time

Benefits offered by this job

Medical, Dental and Vision Insurance (

401(k) Retirement Savings Matching

Paid Time Off

Job summary

EPAM Systems is seeking an experienced Applied AI Senior Product Manager to lead end-to-end lifecycle of AI-powered products, defining strategy, vision, and roadmaps that unlock high-value AI opportunities across GenAI, ML, search, and automation.

You will partner with engineering, data, design, and AI/ML teams to shape requirements, evaluation criteria, and guardrails, while guiding a team of product owners to deliver measurable business impact and responsible AI practices.

Qualifications

• 5+ years in product management, end-to-end ownership of products and launches.
• Proven experience delivering AI-powered products or features (GenAI, ML, search, automation).
• Solid AI literacy, including capabilities, limitations, failure modes, and pricing.
• Expertise across multiple business domains (3+).
• Daily practical use of AI across research, discovery, analysis, documentation, and prototyping.

Responsibilities

• Own product strategy, vision, and roadmap for AI-powered solutions.
• Manage backlogs, release cycles, and cross-product dependencies with AI economics in mind.
• Collaborate with engineering, data, design, and AI/ML teams to define requirements and guardrails.
• Influence stakeholders up to VP level and lead product launches.
• Lead a team of Product Owners/Managers and promote responsible AI practices.

Skills

AI product management

AI literacy

business-domain expertise

product strategy & roadmaps

cross-functional leadership

Job description

EPAM Systems is seeking an experienced Applied AI Senior Product Manager to lead end-to-end lifecycle of AI-powered products, defining strategy, vision, and roadmaps that unlock high-value AI opportunities across GenAI, ML, search, and automation.

You will partner with engineering, data, design, and AI/ML teams to shape requirements, evaluation criteria, and guardrails, while guiding a team of product owners to deliver measurable business impact and responsible AI practices.