Senior Technical Product Manager leading Bot Detection offering strategy at Fingerprint. Owns product execution, roadmap, and commercial outcomes in an AI-automated world.
Responsibilities
Own the strategy and execution of Fingerprint’s Bot Detection offering
Set mission, vision, and strategy for Bot Detection as a distinct product line
Own the roadmap across detection capabilities, taxonomy/identity models, customer-facing UX, and go-to-market readiness
Drive the plan for expanding and improving detection coverage
Partner with Engineering and Data Science to define evaluation methodology, quality targets, and iteration loops
Define how we evolve from “bot detection” toward automation + intent intelligence
Drive strategy for our Automation Intelligence API
Define and ship customer-facing product surfaces for Bot Detection
Partner with Sales, CS, and Marketing to define value messaging and positioning
Operate as the “single-threaded owner” across Product, Engineering, Data Science, Design, GTM, and Customer Success
Requirements
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.
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