Sr Technical Product Manager Bot Ai Automation Intelligence

## 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. Location / level: Remote-friendly (Americas → Central European time zones preferred). ## What you'll own ### 1) 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). ### 2) 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. ### 3) "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. ### 4) 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. ### 5) Commercialization & GTM readiness (in partnership) - 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). ### 6) 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. ## Key outcomes (examples) - Material improvement in detection coverage and quality (including faster iteration on reported gaps). - A cohesive, easy-to-adopt product experience in Dashboard + API, with clear plan-gated paths. - Launches that are sequenced with enablement, documentation, and customer feedback loops. ## What you bring - 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. ## Strongly preferred (technical fluency) - 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.