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About This Role
About the Role
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We're looking for an experienced Senior/Staff Product Manager to become the founding Product Manager at our fast\-growing, seed\-stage company. In this role, you'll partner closely with the CEO, CTO, Engineering, and customers to shape the future of our enterprise AI platform.
This is far more than a traditional roadmap role. You'll own enterprise customer engagements from pre\-sales through post\-sales, translate complex customer problems into scalable product solutions, and help define the product strategy for a rapidly growing company.
We're looking for someone who thrives in ambiguity, enjoys working directly with enterprise customers, and can bridge business, product, and engineering with equal confidence.
Location
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- Hybrid – San Francisco, CA
- Full\-time
Compensation \& Benefits
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### Compensation
- $190,000 – $270,000 base salary
- Level (Senior vs. Staff) determined during the interview process based on experience and performance.
- Meaningful founding\-level equity in a seed\-stage company.
### Benefits
- Best\-in\-class Medical, Dental, and Vision insurance
- 401(k) with up to 4% company match
- $1,200 annual Learning \& Development stipend
- Flexible PTO
- Catered lunches
- Commuter benefits
- Visa sponsorship and relocation support available for qualified candidates
About the Company
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We're a 19\-person, venture\-backed startup building enterprise AI software for highly regulated industries.
- Raised $10M from Lightspeed Ventures and Valor Equity Partners
- AI\-native engineering culture
- Building mission\-critical enterprise software
- Opportunity to join as the company's first Product Manager and help define product strategy from the ground up
What You'll Do
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- Lead enterprise customer engagements from pre\-sales discovery through post\-sales expansion.
- Design and deliver customized product demonstrations tailored to each customer's workflows and business objectives.
- Work directly with enterprise customers to understand complex business problems and translate them into scalable product solutions.
- Partner closely with the CEO, CTO, Engineering, and domain experts to define product strategy and priorities.
- Write detailed Product Requirements Documents (PRDs), engineering briefs, and functional specifications.
- Build rapid prototypes using modern AI coding tools such as Cursor, GitHub Copilot, and Claude to validate ideas.
- Drive multiple enterprise implementations simultaneously while ensuring outstanding customer experience.
- Identify common customer needs and convert them into scalable product capabilities.
- Own complex platform functionality including:
+ Authentication
+ Role\-Based Access Control (RBAC)
+ Approval workflows
+ Data governance
+ API integrations
- Help shape the long\-term product roadmap as the company scales.
Required Qualifications
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- 5–10 years of Product Management experience.
- 5\+ years building enterprise or B2B software products.
- Proven experience owning products throughout the full product lifecycle.
- Strong customer\-facing experience including:
+ Enterprise discovery
+ Solution design
+ Product demonstrations
+ Post\-sales partnership
- Experience translating customer requirements into actionable engineering deliverables.
- Excellent written communication skills with demonstrated experience writing:
+ Product Requirements Documents (PRDs)
+ Functional specifications
+ Engineering briefs
- Strong collaboration skills across Product, Engineering, Executive Leadership, and customers.
- Bachelor's degree required.
Preferred Qualifications
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Experience in one or more of the following areas:
- Enterprise Software
- DevOps Platforms
- Security Software
- Infrastructure Software
- Data Analytics Platforms
- APIs \& Integrations
- AI\-powered enterprise applications
- Regulated industries (Insurance, FinTech, Healthcare, Compliance)
Additional strengths include:
- Startup experience (Seed through Series C)
- Consulting background
- Prior engineering experience
- Experience building products from scratch
- Strong understanding of enterprise architecture and technical integrations
Salary Context
This $190K-$270K range is above the 75th percentile 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 Glint Tech Solutions, 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 $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 ($230K) sits 6% above the category median. Disclosed range: $190K to $270K.
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.
Glint Tech Solutions AI Hiring
Glint Tech Solutions has 3 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer. Positions span San Francisco, CA, US, Sunnyvale, CA, US. Compensation range: $250K - $270K.
Location Context
AI roles in San Francisco pay a median of $277,088 across 810 tracked positions. That's 27% above the national 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.
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