Sr Technical Product Manager, Bot & AI Automation Intelligence
- Role
- Product
- Experience
- Senior
- Company size
- Startup
Open to Worldwide. Set where you work from to check your eligibility.
No BS summary
Senior technical product manager for bot detection, fraud/abuse platforms, and AI automation intelligence. Needs 3+ years in or deep familiarity with bot management/fraud/abuse, strong data-informed product execution, and comfort with detection metrics like precision/recall and false positives/negatives. Remote, Americas to Central European time zones preferred; must be authorized to work from home location and no visa sponsorship.
Fingerprint empowers developers to stop online fraud at the source. We work on turning radical new ideas in the fraud detection space into reality. Our products are developer-focused and our clients range from solo developers to publicly traded companies. We are a globally dispersed, 100% remote company with a strong open-source focus. Our flagship open-source project is FingerprintJS (27K stars on GitHub). We have raised $77M and are backed by Craft Ventures (previously invested in Tesla, Facebook, Airbnb ), Nexus Venture Partners (previously invested in Postman , Apollo.io, MinIO , Druva) and Uncorrelated Ventures (previously invested in Redis, Rollbar & Gradle ). We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Fingerprint recruiting email communications will always come from the @fingerprint.com domain. Any outreach claiming to be from Fingerprint via other sources should be ignored. 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. For US-based employees , the cash base compensation range for this role is $144,000 - $195,000. We set standard ranges for all US roles based on function, level, and geographic location, benchmarked against similar stage growth companies. To comply with local legislation and provide greater transparency to candidates, we share salary ranges on all job postings regardless of desired hiring location. However, these ranges are specific to the hiring location and may differ within or outside the US. Final offer amounts are determined by multiple factors, including geographic location as well as candidate experience and expertise, and may vary from the amounts listed above. We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Fingerprint recruiting email communications will always come from the @fingerprint.com domain. Any outreach claiming to be from Fingerprint via other sources should be ignored. Offers vary depending on, but not limited to, relevant experience, education, certifications/licenses, skills, training, and market conditions. Due to regulatory and security reasons, there’s a small number of countries where we cannot have Fingerprint teammates based. Additionally, because Fingerprint is an all-remote company and people can join our workforce from almost any country, we do not sponsor visas. Fingerprint teammates need to be authorized to work from their home location . We are dedicated to creating an inclusive work environment for everyone. We embrace and celebrate the unique experiences, perspectives and cultural backgrounds that each employee brings to our workplace. Fingerprint strives to foster an environment where our employees feel respected, valued and empowered, and our team members are at the forefront in helping us promote and sustain an inclusive workplace. We highly encourage people from underrepresented groups in tech to apply. If you are applying as a resident of California, please read our CCPA notice here If you are applying as a resident of the EU, please read our GDPR notice here
What you'll do
- 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 the product evolves from “bot detection” toward automation + intent intelligence, covering AI assistants, agentic traffic, direct-to-API automation, and emerging adversarial techniques.
- Drive the plan for expanding and improving detection coverage, such as anti-detect browsers, network and IP intelligence, AI assistant detection, and agentic automation patterns.
- Partner with Engineering and Data Science to define evaluation methodology, quality targets, and iteration loops for false positives/false negatives, coverage, and robustness.
- Own the detection taxonomy and classification semantics, such as good / bad / unknown automation, spoofed identity patterns, and verified/signed bots where relevant.
- Translate competitive and threat landscape trends into prioritized detection investments.
- Drive strategy for the 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.
- Working with other product managers, define and ship customer-facing product surfaces for Bot Detection, including Dashboard experiences, APIs and schema contracts, and 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.
- 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.
- 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.
What they require
- 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, including alignment, prioritization, and execution.
- Customer empathy and ability to translate customer problems into roadmap and requirements.
- Strong data-informed decision making, including 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.
- Preferred: Deep understanding of web technologies and automation techniques, browser + API automation, and how detection systems behave under adversarial pressure.
- Preferred: Understanding of network and IP intelligence, including residential proxies and modern spoofing and tampering techniques.
- Preferred: Familiarity with detection signal pipelines, client-side instrumentation, server-side ingestion, feature engineering, and operating constraints such as latency, scale, robustness.
- Preferred: Experience with build vs buy evaluations in security/detection domains and translating the outcome into an execution plan.
- Preferred: Familiarity with privacy/security constraints and global compliance considerations, e.g., GDPR/CCPA, as applied to detection signals.
- Preferred: Experience building products that combine heuristic + ML approaches, and defining measurement for both.
- Fingerprint teammates need to be authorized to work from their home location.
Fingerprint empowers developers to stop online fraud at the source. Globally dispersed, 100% remote company focused on fraud detection with open-source emphasis.