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WHY DO WE NEED YOU?
This execution-oriented position will play a critical role in the realization of the Infrastructure & Commercial Product Group (ICPG) growth strategy. Supporting the full ICPG portfolio, this includes the coordination and project management of priority initiatives with an emphasis on commercial execution, process improvement and the effective adoption of GenAI tools.
This project manager will be relied upon for effective communication, including with senior team members, BU general managers and functional experts. Managing multiple initiatives simultaneously and without direct reports, a successful candidate will rely upon their ability to connect, influence and support colleagues within ICPG and across the broader organization to obtain successful project outcomes. Supported by an internal champion on each project, they will lead the appropriate resources through all phases of a project, including scoping, planning, execution, completion/hand-off and post-mortem process improvement. They will be relied upon to effectively communicate project status, risks, mitigation and timeline, contributing directly to progress and/or escalating as required to ensure project teams meet or exceed stated objectives. Project duration will vary.
In parallel with project execution activities, this role will help to guide ICPG’s acceleration of GenAI adoption. This includes supporting the development of a GenAI roadmap (in concert with ICPG leadership) and the execution of priority GenAI implementation projects. Considered a vital component of ICPG’s growth strategy, it is expected that up to 50% of this role will be supporting the identification, justification and execution of projects in this dynamic space.
This role requires strong judgement, an openness to debate, the ability prioritize and a willingness to effectively navigate both ambiguity and conflict.
IS THIS JOB FOR YOU? Essential Functions:
Project Management and Coordination
- Define project scope, goals, and deliverables in collaboration with management, project sponsors, relevant functional experts and other stakeholders.
- Effectively communicate expectations to project team members and stakeholders in a timely and clear fashion, continuously manage objectives, and hold project team members accountable for delivery.
- Develop and track relevant project metrics to ensure alignment with objectives (outcome, budget, timeline). Intervene and escalate as required.
- Lead execution by helping project teams maintain an overall project vision with supporting detailed project plans.
- Proactively manage changes in project scope, identify potential roadblocks and devise contingency plans and mitigation.
- Maintain forward progress by making clear recommendations with incomplete information - maintaining optionality and managing risk through frequent and effective communication.
- Develop and deliver progress reports to management and project stakeholders including issue/action item logs, project status cards, risks and recommended/active mitigation.
- Conduct real-time and post-project reviews to recommend and make process adjustments in the spirit of continuous improvement.
- As required to execute the above, coordinate travel logistics, meeting requirements, deployment of collaboration tools, etc.
GenAI Project Portfolio & Project Management
- Contribute to the development of a GenAI roadmap for ICPG, coordinated and aligned with broader SGNA and Saint-Gobain global initiatives. This includes developing a framework (in conjunction with subject matter experts) to identify, screen and define projects/opportunities.
- Work with ICPG stakeholders to review project opportunities, define objectives, quantify expected impacts and prioritize resources – coordinating with SGNA IT as required.
- As projects are selected, serve as project manager for approved and justified ICPG GenAI projects (see project management expectations above). Legal Statement
Saint-Gobain provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state and local laws. Saint-Gobain is an equal opportunity employer of individuals with disabilities and supports the hiring of veterans.
A LITTLE MORE ABOUT US
Saint-Gobain provides a comprehensive Total Rewards package designed to support employees and their families. We believe in the importance of pay transparency and are committed to providing candidates with clear compensation information.
The salary range for this position is $111,00 to $177,000 annually. In addition to base salary, this position is eligible for an annual incentive bonus. The total target cash range for this position, including base salary and target bonus, is $127,600 to $203,500.
Actual compensation will vary based on factors such as location, experience, education, skills, internal equity, and business needs. Bonus payments are based on company and individual performance and are not guaranteed.
Job Reference: USA15652
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 9,079 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Saint-Gobain, 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 947 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Saint-Gobain AI Hiring
Saint-Gobain has 2 open AI roles right now. They're hiring across Research Engineer, AI Product Manager. Positions span Northborough, MA, US, Remote, US. Compensation range: $139K - $139K.
Remote Work Context
Remote AI roles pay a median of $188,000 across 2,316 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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