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The Tech Ex Labs Product Manager helps shape and deliver the roadmap for the firm's proprietary software assets and AI capabilities, translating market and client needs into scalable, secure, responsible AI\-enabled products.
Responsibilities
AI Product Strategy and Roadmap
- Support the product vision, roadmap, and outcome measures for proprietary software assets and AI capabilities.
- Use market trends, client feedback, emerging AI capabilities, and product performance to inform priorities.
Product Discovery and Requirements
- Own defined areas of the product backlog, including release planning, user stories, and acceptance criteria.
- Translate business problems and user needs into clear requirements for engineering, data, AI/ML, and asset teams.
- Recommend tradeoffs that balance speed, value, quality, technical debt, security, compliance, and responsible AI.
Delivery, Readiness, and Performance
- Facilitate sprint planning, backlog refinement, reviews, and delivery ceremonies to meet roadmap goals and KPIs.
- Partner with product design, engineering, AI/ML, data, and asset teams to shape initiatives, epics, and stories.
- Track delivery, adoption, quality, and performance; support UAT, defect resolution, release readiness, and post\-launch measurement.
Stakeholder Collaboration, Adoption, and Responsible AI
- Serve as a product liaison across business stakeholders, AI architects, engineers, product designers, governance, and success teams.
- Gather and prioritize requirements from internal users, client\-facing teams, asset teams, and AI development teams.
- Support adoption through enablement, training, best practices, change management, feedback loops, and stakeholder communication.
- Incorporate responsible AI requirements into features and release criteria, including transparency, monitoring, data quality, oversight, and controls.
Innovation and Continuous Improvement
- Stay current on emerging AI, MLOps, data, cloud, and automation technologies relevant to the firm's software assets.
- Identify opportunities to improve user experience, developer productivity, reliability, and repeatable delivery patterns.
- Champion a product mindset focused on customer experience, measurable outcomes, reusable capabilities, and continuous improvement.
Qualifications
- Bachelor's degree in Business, Computer Science, Engineering, Information Systems, Data Science, or related field preferred; equivalent experience accepted.
- 5\+ years of experience in product management, product ownership, technology delivery, platform management, AI/ML programs, or related disciplines.
- 1\-2\+ years supporting AI, machine learning, analytics, data platforms, cloud products, generative AI, agentic AI, or AI\-enabled software.
- Strong understanding of Agile/Scrum delivery and experience working with cross\-functional Agile teams.
- Track record supporting customer\-centric technology products aligned to business objectives, adoption goals, and measurable outcomes.
- Experience collaborating with engineering, architecture, data, AI/ML, design, governance, business, and stakeholder teams.
- Ability to travel as needed for team meetings, workshops, stakeholder sessions, or conferences.
Knowledge and Skills
AI and Technology Knowledge
- Working understanding of the AI/ML lifecycle, including data ingestion, model development, evaluation, deployment, monitoring, and improvement.
- Familiarity with generative AI, agentic AI, AI platform architecture, MLOps, cloud\-native technologies, and enterprise technology ecosystems.
- Working knowledge of data engineering, platform engineering, AI governance, security, compliance, privacy, and responsible AI frameworks.
Product Management Skills
- Strong roadmap support, backlog prioritization, release planning, and metrics\-driven decision\-making skills.
- Ability to translate business needs into requirements, technical capabilities, user stories, acceptance criteria, and success metrics.
- Strong analytical and problem\-solving skills using customer feedback, performance metrics, and adoption data.
- Ability to balance stakeholder priorities while maintaining focus on value, feasibility, risk, and delivery outcomes.
Leadership and Communication Skills
- Strong stakeholder management, communication, facilitation, and organizational skills.
- Ability to coordinate cross\-functional decisions across business, product, design, engineering, data, AI/ML, and governance teams.
- Ability to communicate product direction clearly and adapt to evolving AI technologies, market trends, and business needs.
Based on pay transparency guidelines, the salary range for this role can vary based on your proximity to one of our West Monroe offices (see table below).
Employees (and their families) are covered by medical, dental, vision, and basic life insurance. Employees are able to enroll in our company’s 401k plan, purchase shares from our employee stock ownership program and be eligible to receive annual bonuses. Employees will also receive unlimited flexible time off and ten paid holidays throughout the calendar year. Eligibility for ten weeks of paid parental leave will also be available upon hire date.
Seattle or Washington, D.C.
$154,400 \- $181,500 USD
Los Angeles
$161,700 \- $190,200 USD
New York City or San Francisco
$169,100 \- $198,800 USD
A location not listed above
$14,700 \- $172,900 USD
### Other consultancies talk at you.
At West Monroe, we work with you.
We’re a global business and technology consulting firm passionate about creating measurable value for our clients, delivering real\-world solutions.
The combination of business and technology is not new, but how we bring them together is unique. We’re fluent in both. We know that technology alone is not the answer, but how we apply it is. We rely on data to constantly adapt and solve new challenges. Actions that work today with outcomes that generate value for years to come.
At West Monroe, we zero in on the heart of the opportunity, getting to results faster and preparing people for what’s next.
You’ll feel the difference in how we work. We show up personally. We’re right there in the room with you, co\-creating through the challenges. With West Monroe, collaboration isn’t a lofty promise, but a daily action. We work together with you to turn vision into clear action with lasting impact.
West Monroeis an Equal Employment Opportunity Employer
We believe in treating each employee and applicant for employment fairly and with dignity. We base our employment decisions on merit, experience, and potential, without regard to race, color, national origin, sex, sexual orientation, gender identity, marital status, age, religion, disability, veteran status, or any other characteristic prohibited by federal, state or local law. To learn more about diversity, equity and inclusion at West Monroe, visit www.westmonroe.com/inclusion. If you require a reasonable accommodation to participate in our recruiting process, please inquire by sending an email to [email protected].
Please review our current policy regarding use of generative artificial intelligence during the application process.
If you are based in California, we encourage you to read West Monroe’s Notice at Collection for California residents, provided pursuant to the California Consumer Privacy Act (CCPA) and linked here.
Salary Context
This $14K-$198K range is in the lower quartile for AI Product Manager roles in our dataset (median: $188K across 140 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 3,708 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At West Monroe, 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 $216,175 based on 270 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($106K) sits 51% below the category median. Disclosed range: $14K to $198K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
West Monroe AI Hiring
West Monroe has 4 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer, AI Product Manager. Based in Chicago, IL, US. Compensation range: $124K - $250K.
Location Context
AI roles in Chicago pay a median of $205,100 across 97 tracked positions. That's 6% below the national median.
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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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