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About This Role
Overview:
We are looking for a Senior Product Manager to help shape the FS-specific strategy, roadmap, requirements, and solutions that leverage Seismic’s horizontal AI capabilities. This role will partner closely with the core AI team and the Product triad—Product, Engineering, and Design—to translate financial services use cases into platform requirements and ensure those capabilities support regulated workflows. The ideal candidate has experience defining product requirements for enterprise SaaS platforms that support AI-enabled workflows in regulated financial services environments, along with a strong passion for AI and financial services and hands-on AI development experience. Success in this role requires building fluency across asset management, wealth management, banking, and insurance, then translating domain-specific needs into practical requirements for compliance-aware AI, personalized engagement, context-driven workflows, and FS-specific intelligence.
Who you are::
- Experience defining product requirements for enterprise SaaS platforms that support AI-enabled workflows in regulated environments; hands-on AI development experience desired.
- Passionate about AI, financial services, and how go-to-market technology helps teams engage customers more effectively.
- Able to turn FS-specific terminology, compliance needs, and workflow context into actionable product requirements.
- Skilled at synthesizing input from SMEs, customers, GTM, compliance, and product teams.
- Working fluency in investment products, vehicles, approvals, disclosures, and eligibility rules.
- Able to reason through regulated content, compliance, supervision, archival, and audit workflows.
- Practical AI fluency, including hands-on exposure to AI development concepts and the ability to translate FS use cases into platform requirements.
- Able to drive FS-specific requirements, clarify roadmap priorities, and coordinate execution with core AI and cross-functional teams.
- Strong in customer discovery, prototype validation, prioritization, and tradeoff communication.
What you'll be doing::
- Define the AI for FS roadmap and translate customer, market, and regulatory needs into clear product requirements.
- Partner with the core AI team to translate FS-specific search, retrieval, relevance, and explainability needs into platform requirements.
- Develop segment-specific requirements across asset management, wealth management, banking, and insurance.
- Drive requirements for FS-specific AI compliance capabilities that support governed content, personalized engagement, and regulated client workflows.
- Coordinate execution with the Product triad and cross-functional partners across AI, Compliance, Content Automation, Digital Outreach, Analytics, and customer-facing teams.
- Partner with Analytics to define FS-specific engagement and content insight requirements that help teams turn intelligence into action, improve go-to-market performance, and measure business outcomes.
- Validate high-value FS use cases, then turn customer and SME feedback into prioritized roadmap decisions and product requirements.
What we have for you::
At Seismic, we’re committed to providing benefits and perks for the whole self. To explore our benefits available in each country, please visit the Global Benefits page.
If you are an individual with a disability and would like to request a reasonable accommodation as part of the application or recruiting process, please click here.
Seismic is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to gender, age, race, religion, or any other classification which is protected by applicable law. :
We are committed to fair and equitable compensation practices.
Seismic's annual base salary range for this position will vary based on applicant's location, experience, job level, skills, and abilities as well as internal equity and alignment market data. The range listed below is the minimum to the maximum of our target hiring range.
Seismic's salary range for this position is: USD $160,000.00/Yr. - USD $180,000.00/Yr.
This position is also eligible to participate in Seismic's incentive plans in addition to base salary. The actual incentive amount will very and will be subject to the terms and conditions set in the applicable incentive plan.
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Salary Context
This $160K-$180K range is below the median for AI Product Manager roles in our dataset (median: $193K across 93 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 8,943 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Seismic, 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 862 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700. This role's midpoint ($170K) sits 23% below the category median. Disclosed range: $160K to $180K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
Seismic AI Hiring
Seismic has 2 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer. Based in US. Compensation range: $180K - $212K.
Location Context
AI roles in Austin pay a median of $207,800 across 271 tracked positions. That's 3% below 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 $253,100 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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