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About This Role
Your Future Evolves Here
Evolent partners with health plans and providers to achieve better outcomes for people with most complex and costly health conditions. Working across specialties and primary care, we seek to connect the pieces of fragmented health care system and ensure people get the same level of care and compassion we would want for our loved ones.
Evolent employees enjoy work/life balance, the flexibility to suit their work to their lives, and autonomy they need to get things done. We believe that people do their best work when they're supported to live their best lives, and when they feel welcome to bring their whole selves to work. That's one reason why diversity and inclusion are core to our business.
Join Evolent for the mission. Stay for the culture.
What You’ll Be Doing:
Job Title: Sr Product Manager (AI Platform)
Evolent is building a new AI platform from the ground up, and this role builds it. The architecture is still being shaped, the first capabilities are moving into production now, and the company is backing the platform as a central piece of its strategy with dedicated product, engineering, applied AI, and data science teams and standing visibility to the executive team. As Sr Product Manager (AI Platform), you will own one of the shared platform workstreams that every AI capability across the company is built on, working shoulder-to-shoulder with architects, applied AI engineers, data scientists, and clinical and operations leaders. Come be part of a mission-driven team building a transformational piece of technology to change how Healthcare is delivered!
Responsibilities
- Lead the product lifecycle for your platform workstream from strategic planning to tactical activities, including ideation, discovery, development, launch, and post-launch analysis.
- Define and articulate the product vision, strategy, and roadmap for your workstream, ensuring alignment with the overall AI platform roadmap, Evolent's company goals, and market trends.
- Conduct thorough market research, competitive analysis, and customer feedback gathering (internal teams and clients) to identify unmet needs and opportunities.
- Translate complex business requirements and user needs into detailed product specifications, user stories, and acceptance criteria.
- Collaborate closely with engineering, architecture, applied AI, data science, design, and other cross-functional teams to ensure successful product development and delivery.
- Prioritize the product backlog and manage feature development, ensuring optimal resource allocation and timely delivery against platform and capability delivery dates.
- Develop and execute go-to-market and adoption strategies, including positioning, messaging, and enablement materials for the internal teams and clients who consume your platform components.
- Monitor product performance, analyze key metrics, and identify areas for improvement and iteration.
- Act as a product evangelist, communicating product value and benefits to internal and external stakeholders.
- Mentor and provide guidance to junior product managers and team members.
- Partner with data science and engineering leaders to define scalable AI architectures, model evaluation frameworks, and production readiness criteria.
- Own definition, execution, and measurement of proof-of-concepts and pilot initiatives to validate emerging technologies.
- Drive decisions regarding AI feature prioritization based on customer value, operational efficiency, and technical feasibility.
Required Qualifications
- Bachelor's degree in a relevant field (e.g., Computer Science, Data Science, Engineering, Business, Healthcare Administration) or equivalent practical experience.
- Minimum 5-7+ years of experience in product management, with a strong emphasis on software products in the healthcare technology sector, including 2+ years owning platform, infrastructure, data, or API products consumed by other engineering teams.
- Proven track record of successfully launching and managing complex software products.
- Demonstrated ability to define and execute product strategy, roadmap, and go-to-market plans.
- Working knowledge of modern AI technologies and the trade-offs among them: model selection, prompting and orchestration approaches, retrieval-augmented generation, fine-tuning versus prompting, and agentic patterns.
- Proven ability to partner with architects and engineers on technical trade-offs, including build versus buy versus partner, canonical data models, and API and event contracts.
- Experience delivering software in a regulated environment with sensitive or protected data (PHI/PII), including audit, traceability, and access-control requirements.
- Strong analytical skills with the ability to interpret data, identify trends, and make data-driven decisions.
- Excellent communication, presentation, and interpersonal skills, with the ability to effectively communicate with technical and non-technical stakeholders.
- Experience with Agile development methodologies (e.g., Scrum, Kanban) and proficiency in product management tools (e.g., JIRA, Confluence, Aha!).
- Ability to thrive in a fast-paced, dynamic environment and manage multiple priorities effectively.
Preferred Qualifications
- Master's degree in a relevant field (e.g., Business, Computer Science, Data Science, Healthcare Administration, Engineering).
- Deep understanding of the healthcare industry, including payer, provider, and value-based care models; experience in prior authorization, utilization management, appeals, or payer and provider clinical operations is a plus.
- Direct experience leading GenAI or machine learning product initiatives from concept through launch, and bringing AI-enabled products to enterprise scale.
- Working knowledge of healthcare interoperability standards such as FHIR, X12 278, and HL7, and of CMS Interoperability and Prior Authorization rules.
- Depth in Microsoft Azure as a primary platform (e.g., AKS, Service Bus, Azure SQL and Cosmos DB, Azure AI Foundry, Azure OpenAI, Document Intelligence, AI Search). Comparable AWS or Google Cloud depth considered.
- Familiarity with event-driven architecture patterns (CloudEvents, event sourcing, decision ledgers and audit trails) and with rules engines delivered as shared services.
- Experience with agent architectures and orchestration frameworks, embedding and retrieval pipelines, document processing (OCR to NLP to embedding to search), and model routing through a centralized AI gateway.
- Knowledge of MLOps and LLMOps practices, including evaluation datasets and scoring, shadow-mode validation, drift and quality monitoring, and observability tooling such as OpenTelemetry.
- Exposure to identity, access, and lifecycle governance for AI systems and agents, and to HITRUST or SOC 2 certification programs.
- Familiarity with data warehouse and analytics technologies such as SQL, Python, Power BI, Tableau, Databricks, or Snowflake.
- Experience collaborating with data scientists on experimentation, model tuning, and deployment strategies.
To ensure a secure hiring process we have implemented several identity verification steps, including submission of a government issued photo ID. We conduct identity verification during interviews, and final interviews may require onsite attendance. All candidates must complete a comprehensive background check, in-person I-9 verification, and may be subject to drug screening prior to employment. The use of artificial intelligence tools during interviews is prohibited and monitored. Misrepresentation will result in immediate disqualification from consideration.
Technical Requirements:
We require that all employees have the following technical capability at their home: High speed internet over 10 Mbps and, specifically for all call center employees, the ability to plug in directly to the home internet router.
Evolent is an equal opportunity employer and considers all qualified applicants equally without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability status. If you need reasonable accommodation to access the information provided on this website, please contact [email protected] for further assistance.
The expected base salary/wage range for this position is $115,000 - 135,000. As part of our total compensation package, Evolent is proud to offer comprehensive benefits (including health insurance benefits) to qualifying employees. All compensation determinations are based on the skills and experience required for the position and commensurate with experience of selected individuals, which may vary above and below the stated amounts.
Salary Context
This $115K-$135K range is in the lower quartile for AI Product Manager roles in our dataset (median: $194K across 123 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 9,079 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Evolent, 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 Required
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. Senior-level AI roles across all categories have a median of $229,300. This role's midpoint ($125K) sits 43% below the category median. Disclosed range: $115K to $135K.
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.
Evolent AI Hiring
Evolent has 3 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager. Based in Remote, US. Compensation range: $135K - $135K.
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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