Interested in this AI Product Manager role at Blue Shield of California?
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Your Role
The Product Manager, Consultant \- Automation \& AI Business Delivery reports to the Transformation Sr. Director. They will lead design and delivery of automation and AI\-driven solutions that streamline operations and improve business outcomes. Define product vision, roadmap, and measurable value (cost, efficiency, CX). Partner cross\-functionally (IT, operations, vendors) to translate needs into scalable solutions, drive delivery, and ensure compliance. Own backlog, prioritize use cases, and track performance. Influence stakeholders, manage risks, and accelerate adoption of AI/automation capabilities across the enterprise.
Our leadership model is about developing great leaders at all levels and creating opportunities for our people to grow – personally, professionally, and financially. We are looking for leaders that are energized by creative and critical thinking, building and sustaining high\-performing teams, getting results the right way, and fostering continuous learning.
Your Work
In this role, you will:
- Write detailed user stories and acceptance criteria covering multiple user\-types.
- Utilize tools for basic analytics to inform product decisions and show measurable outcomes of product releases
- Drive trade\-off discussions between scope and schedule Identify risks within a product and develop mitigation plans
- Own demand intake alignment and delivery prioritization for platform capabilities
- Manage product backlogs aligned to automation/AI roadmap across platforms
- Drive delivery discipline (velocity, quality, predictability)
- Own demand intake alignment and delivery prioritization execution
- Manage product backlogs aligned to enterprise roadmap
- Drive delivery discipline (velocity, quality, predictability)
- Support business requirements gathering by validating capabilities and platform\-based solution for automation/AI
- Create and manage capabilities maturity tracking for automation/AI features
- Manage end\-to\-end delivery lifecycle from intake through deployment
- Lead product management for automation and AI\-enabled solutions across platforms such as SmartComms and Pega, driving strategy, delivery, and continuous optimization
- Drive execution governance and backlog management for automation and AI capabilities, ensuring prioritized delivery and successful platform deployment
- Validate outcomes and progress to commitments post\-delivery
Your Knowledge and Experience
- Minimum 6 years of experience in Product Management, Management Consulting, or Entrepreneurship required.
- Requires a BA/BS in Business, Finance, Economics, Public Health, or Information Technology, or equivalent experience.
Graduate degree (e.g. MBA) is highly desirable.
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Hybrid
This role requires employees to be in\-office based on our hybrid workplace model, balancing purposeful in\-person collaboration with flexibility. For most teams, this means coming into the office two days each week.
Employees living more than 50 miles from an office location will work with their manager to determine in\-office time based on business need.
**ABOUT THE TEAM
About Blue Shield of California**
As of January 2025, Blue Shield of California became a subsidiary of Ascendiun. Ascendiun is a nonprofit corporate entity that is the parent to a family of organizations including Blue Shield of California and its subsidiary, Blue Shield of California Promise Health Plan; Altais, a clinical services company; and Stellarus, a company designed to scale healthcare solutions. Together, these organizations are referred to as the Ascendiun Family of Companies.
At Blue Shield of California, our mission is to create a healthcare system worthy of our family and friends and sustainably affordable. We are transforming health care in a way that genuinely serves our nonprofit mission by lowering costs, improving quality, and enhancing the member and physician experience.
To achieve our mission, we foster an environment where all employees can thrive and contribute fully to address the needs of the various communities we serve. We are committed to creating and maintaining a supportive workplace that upholds our values and advances our goals.
Blue Shield is a U.S. News Best Company to work for, a Deloitte U.S. Best Managed Company and a Top 100 Inspiring Workplace. We were recognized by Fair360 as a Top Regional Company, and one of the 50 most community\-minded companies in the United States by Points of Light. Here at Blue Shield, we strive to make a positive change across our industry and communities – join us!
Our Values:
- Honest. We hold ourselves to the highest ethical and integrity standards. We build trust by doing what we say we're going to do and by acknowledging and correcting where we fall short.
- Human. We strive to listen and communicate effectively, showing empathy by understanding others' perspectives.
- Courageous. We stand up for what we believe in and are committed to the hard work necessary to achieve our ambitious goals.
Our Workplace Model
We believe in fostering a workplace environment that balances purposeful in\-person collaboration with flexibility \- providing clear expectations while respecting the diverse needs of our workforce. Our workplace model is designed around intentional in\-person interaction, collaboration, connection, creativity and flexibility:
- For most teams, this means coming into the office two days per week.
- Employees living more than 50 miles from an office location, out of state employees, and employees in certain member\-facing roles should work with their manager to determine in\-office time based on business need.
- For employees with medical conditions that may impact their ability to work in\-office, we are committed to engaging in an interactive process and providing reasonable accommodations to ensure their work environment is conducive to their success and well\-being.
The Company reserves the right to require more presence in the office based on business needs, and requirements are subject to change with periodic reviews.
Physical Requirements:
Office Environment \- roles involving part to full time schedule in Office Environment. Based in our physical offices and work from home office/deskwork \- Activity level: Sedentary, frequency most of work day.
Equal Employment Opportunity:
External hires must pass a background check/drug screen. Qualified applicants with arrest records and/or conviction records will be considered for employment in a manner consistent with Federal, State and local laws, including but not limited to the San Francisco Fair Chance Ordinance. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, national origin, sexual orientation, gender identity, protected veteran status or disability status and any other classification protected by Federal, State and local laws.
Salary Context
This $123K-$184K range is in the lower quartile for AI Product Manager roles in our dataset (median: $187K across 164 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 4,133 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Blue Shield of California, 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 $213,800 based on 610 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,778. This role's midpoint ($153K) sits 28% below the category median. Disclosed range: $123K to $184K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
Blue Shield of California AI Hiring
Blue Shield of California has 1 open AI role right now. They're hiring across AI Product Manager. Based in El Dorado Hills, CA, US. Compensation range: $184K - $184K.
Location Context
Across all AI roles, 14% (583 positions) offer remote work, while 3,532 require on-site attendance. Top AI hiring metros: New York (2,760 roles, $211,000 median); San Francisco (2,258 roles, $253,000 median); Los Angeles (1,841 roles, $195,000 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 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 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 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). 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 (1,901) and senior (1,663) 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 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 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 $200,700. Top-quartile roles start at $254,000, and the 90th percentile reaches $307,500. 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 $274,200 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 (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 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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