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Role Description

We are looking for a Senior AI Product Manager to work with SAIL , owning the path from experimentation to real-world impact for advanced AI and ML initiatives. This role sits at the intersection of applied research, productization, and business impact.

• Help turn cutting-edge models and techniques into outcomes that Risk teams can trust, Engineering teams can scale, and customers can ultimately benefit from.
• Deeply comfortable with ambiguity and understands how to translate model performance into business value.
• Drive alignment across Data Science, Engineering, Risk, and GTM without slowing momentum.
• Focus on decisioning quality, scalability, cost, latency, and downstream impact.

Responsibilities

• Create Clarity on Impact & Outcomes:
  • Translate experimental and model-level results into clear business impact (e.g., fraud loss reduction, automation lift, approval-rate improvements, operational efficiency).
  • Define what “success” means for each AI technique or model before it reaches production.
  • Frame why the work matters to internal stakeholders including Risk, Customer Success, Sales, Finance, and Executive Leadership.
• Own the Path from Experimentation to Production:
  • Partner with Data Science to move models from offline experimentation to online testing and controlled rollout.
  • Help define evaluation frameworks, guardrails, and decision thresholds required for production use.
  • Ensure trade-offs (accuracy, latency, cost, operational complexity) are explicit and intentional.
• Drive Cross-Functional Alignment:
  • Act as the primary product interface between SAIL, Risk, and Engineering.
  • Ensure there is a predictable process for ramping traffic, managing risk approvals, and resolving blockers.
  • Secure engineering capacity and infrastructure alignment by grounding asks in committed outcomes and timelines.
• Build the “Path to Customer” for New AI Capabilities:
  • Identify which customer segments or merchants are realistic early adopters for new decisioning approaches.
  • Define the value story: what problem is solved, how success is measured, and what changes operationally for the customer.
  • Partner with Customer Success to estimate upside, prerequisites, and deployment complexity.
• Execution, Communication, and Accountability:
  • Maintain a clear view of milestones, dependencies, risks, and decisions across active SAIL initiatives.
  • Keep stakeholders informed with the right level of detail to sustain momentum without over-communicating.
  • Ensure experimental work does not stall due to ambiguity, misalignment, or lack of ownership.

What You’ll Work On (Examples)

• Translating advanced AI and ML experiments into clear product narratives and deployment plans.
• Defining how new decisioning approaches integrate into existing systems, workflows, and risk controls.
• Helping standardize evaluation, comparison, and rollout criteria across different modeling approaches.
• Aligning model innovation with infrastructure realities such as cost budgets, latency constraints, and scalability requirements.
• Ensuring internal teams understand what SAIL is building, when it will matter, and how it will show up for customers.

Qualifications

• 6+ years of Product Management experience, with significant exposure to AI- or ML-driven products.
• Proven experience working closely with Data Science and Engineering on model-centric systems.
• Strong ability to translate technical performance into business and customer outcomes.
• Comfort operating in highly ambiguous, fast-moving environments.
• Excellent written and verbal communication skills across technical and non-technical audiences.
• Strong sense of ownership, judgment, and bias toward action.

Nice to have:

• Experience with decisioning systems, risk models, or large-scale ML platforms.
• Familiarity with model evaluation, experimentation frameworks, and feedback loops.
• Experience working in fraud, risk, trust & safety, or operationally-constrained environments.
• Background in scaling early or experimental products into production systems.

Benefits

• Discretionary Time Off Policy (Unlimited!)
• 401K Match
• Stock Options
• Annual Performance Bonus or Commissions
• Paid Parental Leave (12 weeks)
• On-Demand Therapy for all employees & their dependents
• Dedicated learning budget through Learnerbly
• Health Insurance
• Dental Insurance
• Vision Insurance
• Flexible Spending Account (FSA)
• Short Term and Long Term Disability Insurance
• Life Insurance
• Company Social Events
• Signifyd Swag

Compensation

• Base Salary Ranges by Pay Zone:
  • Tier 1 (NYC/SF Bay Area/Seattle): $165,000 – $205,000 annually
  • Tier 2 (DC Metro/Austin/Chicago/Denver/Boston/Los Angeles/San Diego): $155,000 – $195,000 annually
  • Tier 3 (US - All Other): $145,000 – $185,000 annually
• This role is eligible for a stock option grant of 6,000-8,000 stock options, based on the position level and internal compensation guidelines.
• This role is eligible for an annual performance bonus of up to 10% of base salary.

Inclusivity Statement

We want to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.