Sr Technical Product Manager, Bot & AI Automation Intelligence - Fingerprint

About Fingerprint

Fingerprint empowers enterprises to detect and stop online fraud with the world’s most accurate device intelligence. We lead our industry with bleeding-edge identification capabilities and work on turning new ideas and discoveries in the fraud detection space into reality. Our customers range from innovative startups to leading enterprise companies, including Plaid, Dropbox, and Booking.com.

Fingerprint is a globally dispersed, 100% remote company. We were named on the 2026 Forbes Best Startup Employers list and ranked #803 on the 2026 Inc. 5000 list of America’s fastest-growing private companies.

We have raised $77M and are backed by Craft Ventures (Tesla, Facebook, Airbnb), Nexus Venture Partners (Postman, Apollo.io, MinIO, Druva) and Uncorrelated Ventures (Redis, Rollbar, Gradle).

About the Role

We’re looking for a Senior Technical Product Manager to own the strategy and execution of Fingerprint’s Bot Detection offering in an increasingly AI-automated world — from defining what we detect (and how we classify intent), to shipping customer-facing product experiences, to driving adoption and commercial outcomes.

Responsibilities

Bot Detection Product Strategy & Roadmap

• Set mission, vision, and strategy for Bot Detection as a distinct product line (including how it fits alongside Identification and Smart Signals).
• Own the roadmap across detection capabilities, taxonomy/identity models, customer-facing UX, and go-to-market readiness.
• Define how we evolve from “bot detection” toward automation + intent intelligence (covering AI assistants, agentic traffic, direct-to-API automation, and emerging adversarial techniques).

Detection Capabilities & Intelligence (The "What We Detect" Layer)

• Drive the plan for expanding and improving detection coverage (e.g., anti-detect browsers, network and IP intelligence, AI assistant detection, agentic automation patterns).
• Partner with Engineering and Data Science to define evaluation methodology, quality targets, and iteration loops (false positives/false negatives, coverage, robustness).
• Own the detection taxonomy and classification semantics (e.g., good / bad / unknown automation, spoofed identity patterns, verified/signed bots where relevant).
• Translate competitive and threat landscape trends into prioritized detection investments.

"Beyond JS" / Edge & Server-Side Automation Detection

• Drive strategy for our Automation Intelligence API, detecting automation without requiring a browser JS agent, including edge / pre-origin and direct HTTP contexts.
• Align data contracts and platform requirements so bot/automation signals are consistent across JS-based and non-JS collection paths.

Customer Experience: Dashboard, APIs, and Developer Workflows

• Working with other product managers, define and ship customer-facing product surfaces for Bot Detection:
  • Dashboard experiences (overview, events, details, export/workflows)
  • APIs and schema contracts (including compatibility where needed)
  • Guidance for integrating Bot Detection into rule engines, fraud tooling, and customer decisioning pipelines
• Own plan gating / packaging assumptions for self-serve vs enterprise experiences.

Commercialization & GTM Readiness

• Partner with Sales, CS, and Marketing to:
  • Define value messaging and positioning
  • Run beta/research preview motions and customer feedback loops
  • Drive launch planning and enablement
• Work cross-functionally on pricing/packaging inputs and operational readiness (while partnering with the owning teams for billing implementation).

Cross-Functional Program Leadership

• Operate as the “single-threaded owner” across Product, Engineering, Data Science, Design, GTM, and Customer Success.
• Run quarterly planning, define clear milestones, manage dependencies, and communicate tradeoffs.

Qualifications

• 3+ years experience at, or deep familiarity with, bot management / fraud / abuse platforms (e.g., Cloudflare, Akamai, HUMAN, Arkose Labs, DataDome, PerimeterX, Sift, etc.).
• High ownership and strong cross-functional operating cadence (alignment, prioritization, and execution).
• Customer empathy and ability to translate customer problems into roadmap and requirements.
• Strong data-informed decision making (defining success metrics, reading dashboards, and partnering with Product Analytics / DS).
• Comfort with measurement and iteration in detection systems: precision/recall tradeoffs, false positive/false negative analysis, coverage targets, and model/rule iteration loops.
• Familiarity with privacy and regulatory constraints (e.g., GDPR/CCPA) as applied to detection signals; ability to drive privacy-preserving product requirements.
• Deep understanding of web technologies and automation techniques (browser + API automation), and how detection systems behave under adversarial pressure.
• Understanding of network and IP intelligence, including residential proxies and modern spoofing and tampering techniques.
• Familiarity with detection signal pipelines (client-side instrumentation, server-side ingestion, feature engineering) and operating constraints (latency, scale, robustness).
• Experience with build vs buy evaluations in security/detection domains (and translating the outcome into an execution plan).
• Familiarity with privacy/security constraints and global compliance considerations (e.g., GDPR/CCPA) as applied to detection signals.
• Experience building products that combine heuristic + ML approaches, and defining measurement for both.

Location & Compensation

• Location: Remote-friendly (Americas to Central European time zones preferred).
• Salary Range: $144,000 - $195,000 USD (dependent on location and experience; e.g., NYC: $170k - $195k, Chicago: $144k - $166k).