Interested in this AI Product Manager role at Expedient?
Apply Now →About This Role
Expedient helps mid\-market and enterprise organizations modernize infrastructure, manage data, and deploy AI safely at scale. We have been in business 25 years, retain 99 percent of our clients, operate under a 100 percent uptime SLA, hold 200\+ active technology certifications, and employ technical staff in 70 percent of roles. We deliver managed cloud, data, and AI under a single operating model: Intelligent Infrastructure.
AI CTRL is Expedient's enterprise AI platform. Prompts, responses, and automated workflows inside a customer's organization are routed, governed, and measured through it.
About the Role:
Secure Gateway and Chat is the entry point to AI CTRL and where most customers begin. It includes a governed model gateway, a multi\-model chat interface, and the customer admin portal.
This role owns that product line: roadmap, requirements, both UI surfaces, and pricing and packaging. You will work with one engineering team and report to the Head of Product.
What You'll Be Doing:
Product and roadmap* Own the multi\-quarter roadmap for the gateway, the chat interface, and the customer admin portal.
- Own ongoing feature development for both UI surfaces, the client\-facing chat experience and the admin portal. This is sustained ownership across releases rather than a single launch.
- Define the admin experience, including SSO and RBAC, model and connector configuration, usage visibility, budget and rate controls, and audit.
- Define the client experience, including model selection, bringing customer data into a prompt, and returning a governed response.
- Write user stories, acceptance criteria, and release scope.
- Partner with engineering leadership on release planning and tradeoffs.
Pricing and packaging* Maintain the SKU catalog and seat tiers, including what is included at each tier, what meters, and where upgrades are triggered.
- Define the credit and consumption model, including unit definition, rate card, overage behavior, and how usage is presented in the admin portal.
- Recommend pricing changes based on competitive and deal data.
Market and customers* Conduct ongoing competitive analysis of enterprise AI platforms and model gateways, and recommend roadmap changes based on what you find.
- Join discovery calls and pilot reviews to stay close to buyers and users.
What We're Looking For:
Required* 5\+ years of B2B product management experience, including at least 3 years owning a SaaS product or a significant product area.
- Experience owning the ongoing feature backlog for both a customer\-facing application and an admin console, with a record of shipping across multiple releases over two or more years.
- Experience owning pricing and packaging decisions such as seat tiers, usage metering, or consumption pricing, including the ability to describe a pricing decision you made and its effect on revenue.
- Working fluency with AI products and concepts
- Working knowledge of SSO, RBAC, observability, vector stores, MCPs and the LLM provider landscape.
- Experience supporting B2B distribution through direct sales, channel partners, or both.
- Comfort making decisions with incomplete information and communicating the reasoning behind them.
Preferred* Experience with model gateways, chat interfaces, or vector and search
- Background in managed services, cloud, or infrastructure SaaS.
- Experience selling to or supporting mid\-market enterprises in the $50M to $2B revenue range.
This is a hybrid position requiring proximity to our office location in Pittsburgh, PA. Sponsorship is not provided for this role.
Salary for this position is directly related to your own experience, knowledge, and skills. Estimated range for this role is $150,000 to $180,000
\#LI\-Hybrid WORKING FOR EXPEDIENT
We prioritize ongoing education and continuous innovation to remain at the forefront of the information technology landscape. Our commitment to learning is reflected in our comprehensive employee training and tuition reimbursement programs, which are driven by our employees and funded by Expedient 100%.
For our full\-time employees we offer an exceptional benefits package including three weeks of paid time off annually that increases with tenure plus your birthday off and a health holiday to be used for preventive care. We offer parental leave, top\-tier medical, dental, and vision, disability and life insurance, at an affordable rate, wellness engagement opportunities, and a 401(k) with a generous match.
We also recognize the importance of a comfortable and convenient work environment. We offer a hybrid work model for many roles, paid parking and other perks.
Expedient is an equal opportunity employer. Qualified applicants will receive fair and equitable consideration for employment without regard to their race, color, religion, national origin, gender, protected veteran status, disability, or any other characteristic protected by law.
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Salary Context
This $150K-$180K range is below the median 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 Expedient, 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. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($165K) sits 24% below the category median. Disclosed range: $150K to $180K.
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.
Expedient AI Hiring
Expedient has 4 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager. Positions span Pittsburgh, PA, US, US. Compensation range: $150K - $250K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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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