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The Tech Ex Labs Senior Product Owner will define and deliver the roadmap for the firm's portfolio of proprietary software assets and AI capabilities. This role partners with business leaders, AI architects, engineers, product design, governance, and product success teams to turn market and client needs into scalable, secure, responsible AI\-enabled products. The ideal candidate brings senior product ownership experience and practical depth in generative AI, agentic AI, machine learning, data platforms, cloud services, and AI governance.
Responsibilities
AI Product Vision and Roadmap
- Define and maintain the vision, strategy, roadmap, and outcome measures for proprietary software assets and AI capabilities.
- Use market trends, client feedback, emerging AI capabilities, competitive signals, and product performance to inform priorities.
Backlog Ownership and Product Requirements
- Own the AI product backlog, including feature prioritization, release planning, feature decomposition, user stories, and acceptance criteria.
- Translate business problems and user needs into clear requirements for engineering, data, AI/ML, and asset delivery teams.
- Make tradeoff decisions that balance speed, value, quality, technical debt, security, compliance, and responsible AI considerations.
Delivery, Readiness, and Performance
- Lead sprint planning, backlog refinement, reviews, and delivery ceremonies to ensure increments meet roadmap goals and KPIs.
- Partner with product design, engineering, AI/ML, data, and platform teams to shape solution approaches for initiatives, epics, and stories.
- Manage delivery, model, data, privacy, security, operational, and adoption risks; support UAT, defect resolution, release readiness, and post\-launch measurement.
Stakeholder Collaboration, Adoption, and Responsible AI
- Serve as the product liaison across business stakeholders, AI architects, data team, ML engineers, asset engineers, product designers, governance, and product success teams.
- Gather, evaluate, and prioritize requirements from internal users, client\-facing teams, asset teams, and AI development teams.
- Drive adoption through enablement, training, best practices, change management, feedback loops, and clear executive communication.
- Embed responsible AI requirements into product features and release criteria, including transparency, auditability, monitoring, data quality, human oversight, and risk controls.
Innovation and Continuous Improvement
- Evaluate emerging AI, MLOps, data, cloud, and automation technologies that could strengthen the firm's proprietary software asset portfolio.
- Identify opportunities to improve developer productivity, reduce operational cost, increase reliability, and standardize repeatable patterns across AI and software assets.
- Champion a product mindset focused on customer experience, measurable business outcomes, reusable capabilities, continuous delivery, and scalable operations.
Qualifications
- Bachelor's degree in Business, Computer Science, Engineering, Information Systems, Data Science, or a related field preferred; equivalent experience accepted.
- 7\+ years of experience in product management, product ownership, technology delivery, platform management, AI/ML programs, or related disciplines.
- 2\+ years of experience supporting AI, machine learning, analytics, data platforms, cloud\-based products, generative AI, agentic AI, or AI\-enabled software capabilities.
- Strong understanding of Agile/Scrum delivery and experience leading cross\-functional Agile teams.
- Proven track record delivering 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 executive stakeholders.
- Ability to travel as needed for team meetings, workshops, stakeholder sessions, or conferences.
Knowledge and Skills
AI and Technology Knowledge
- Practical understanding of the AI/ML lifecycle, including data ingestion, model development, evaluation, deployment, monitoring, retraining, and continuous improvement.
- Familiarity with generative AI, agentic AI concepts, 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 Ownership Skills
- Strong product strategy, roadmap development, backlog prioritization, release planning, and metrics\-driven decision\-making skills.
- Ability to translate ambiguous business needs into product requirements, technical capabilities, user stories, acceptance criteria, and success metrics.
- Strong analytical and problem\-solving skills, with the ability to use customer feedback, performance metrics, and adoption data to guide product decisions.
- Ability to balance competing stakeholder priorities while maintaining focus on business value, feasibility, risk, and delivery outcomes.
Leadership and Communication Skills
- Excellent stakeholder management, executive communication, facilitation, and organizational skills.
- Ability to lead cross\-functional decision\-making across business, product, design, engineering, data, AI/ML, and governance teams.
- Ability to communicate a compelling product vision and adapt quickly 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.
$194,100 \- $228,400 USD
Los Angeles
$203,400 \- $239,300 USD
New York City or San Francisco
$212,600 \- $250,100 USD
A location not listed above
$184,900 \- $217,500 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 $203K-$250K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $180K across 1841 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At West Monroe, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. Disclosed range: $203K to $250K.
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/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
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).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
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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