Senior Product Manager in London

At Signifyd, we help merchants confidently grow their businesses by building trusted relationships with their customers. Our advanced technology, combined with a team genuinely invested in our clients’ success, creates frictionless shopping experiences, approving more good orders, protecting revenue, and keeping customers happy. Trusted by thousands of leading merchants across more than 100 countries, we securely process billions of transactions each year. Our people are the heart of everything we do, driving our mission forward with commitment, empathy, and creativity. Join us on our mission to empower fearless commerce by helping online retailers provide superior customer experiences and eliminate fraud.

Signifyd AI Lab (SAIL) is our applied AI and machine‑learning innovation group. SAIL partners closely with Risk, Engineering, and Data Science to develop and productionize next‑generation decisioning techniques that materially improve fraud outcomes, automation, and customer experience across Signifyd’s platform.

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. You will help turn cutting‑edge models and techniques into outcomes that Risk teams can trust, Engineering teams can scale, and customers can ultimately benefit from.

The ideal candidate is deeply comfortable with ambiguity, understands how to translate model performance into business value, and can drive alignment across Data Science, Engineering, Risk, and GTM without slowing momentum. This is not a feature PM role. It is a systems‑and outcomes‑oriented role, focused on decisioning quality, scalability, cost, latency, and downstream impact.

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.

Requirements

• 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 in our US offices

• 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
• Vision Insurance
• Flexible Spending