Interested in this AI Product Manager role at EPAM Systems?
Apply Now →About This Role
We are looking for an experienced and forward-thinking Applied AI Senior Product Manager to lead the end-to-end lifecycle of cutting-edge AI-powered products and features. In this role, you will own the product strategy, vision, and roadmap, driving innovation by identifying and justifying high-value AI opportunities (such as GenAI, ML, search, and automation) that deliver exceptional business and customer value.
Req.#1100332225
Responsibilities
- Strategy & Vision: Own product strategy, vision, roadmap, and market analysis—clearly identifying and justifying where AI adds tangible value
- Lifecycle & Execution: Manage backlogs, cross-product dependencies, release cycles, and support models while balancing cost, latency, and quality trade-offs for AI economics
- Cross-Functional Collaboration: Partner effectively with engineering, data, design, and AI/ML teams to define requirements, use cases, evaluation criteria, quality bars, and guardrails
- Stakeholder Influence: Influence stakeholders up to and including the VP level, leading all critical aspects of product launches
- Leadership & AI Proficiency: Lead a team of Product Owners/Managers across a product line, elevating the team's practical AI proficiency and promoting responsible AI practices (privacy, bias, security, transparency)
Requirements
- Product Management Experience: 5+ years in Product Management, having successfully managed products end-to-end (including post-launch maintenance) and launched multiple products/capabilities to market
- AI Product Track Record: At least one proven experience delivering or materially improving an AI-powered product or feature (e.g., GenAI, ML, recommendations, search, or automation)
- AI Literacy & Commercial Acumen: Solid working AI literacy regarding current capabilities, limitations, and failure modes, coupled with familiarity with product profitability, competitive positioning, and pricing
- Business Domain Expertise: Expertise across multiple (3+) business domains, enabling you to act as a credible business-domain SME
- Applied AI Skills & Adaptability: Daily practical use of AI across research, discovery, analysis, documentation, and prototyping, with continuous adaptability as AI tools evolve
We offer
- Medical, Dental and Vision Insurance (Subsidized)
- Health Savings Account
- Flexible Spending Accounts (Healthcare, Dependent Care, Commuter)
- Short-Term and Long-Term Disability (Company Provided)
- Life and AD&D Insurance (Company Provided)
- Employee Assistance Program
- Unlimited access to LinkedIn learning solutions
- Matched 401(k) Retirement Savings Plan
- Paid Time Off – the employee will be eligible to accrue 15-25 paid days, depending on specific level and tenure with EPAM (accrual eligibility may change over time)
- Paid Holidays - nine (9) total per year
- Legal Plan and Identity Theft Protection
- Accident Insurance
- Employee Discounts
- Pet Insurance
- Employee Stock Purchase Program
- If otherwise eligible, participation in the discretionary annual bonus program
- If otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program
For remote work in New York City only.
EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our clients, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.
Engineer the Future with a Career at EPAM
This posting includes a good faith range of the salary EPAM would reasonably expect to pay the selected candidate. The range provided reflects base salary only. Individual compensation offers within the range are based on a variety of factors, including, but not limited to: geographic location, experience, credentials, education, training; the demand for the role; and overall business and labor market considerations. Most candidates are hired at a salary within the range disclosed. Salary range: $130,000 - $200,000. In addition, the details highlighted in this job posting above are a general description of all other expected benefits and compensation for the position.
Applications will be accepted on a rolling basis.
EPAM will not provide new H-1B visa sponsorship for this position. Candidates with existing transferable H-1B status may be considered.
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Salary Context
This $130K-$200K range is below the median for AI Product Manager roles in our dataset (median: $193K across 99 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 9,653 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At EPAM Systems, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills in Demand for This Role
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $220,200 based on 862 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700. This role's midpoint ($165K) sits 25% below the category median. Disclosed range: $130K to $200K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
EPAM Systems AI Hiring
EPAM Systems has 14 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer, AI Consultant, AI Software Engineer. Positions span Remote, US, Houston, TX, US, New York, NY, US. Compensation range: $90K - $260K.
Remote Work Context
Remote AI roles pay a median of $185,906 across 2,124 positions. About 6% of all AI roles offer remote work.
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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