Want to know if this job is worth applying to?
San Francisco, California, United States
Onsite
Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.
We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading.
We are looking for a Senior Technical Product Manager to join our Digital Intelligence team and lead the evolution of our Device Recognition products. In this role, you will own the technology that recognizes devices across sessions, customers, and channels, and binds them to verified identity through Socure's Global Device ID and Identity Graph. You will define how we collect signals through our Web and Mobile SDKs, how we build durable device fingerprints across browsers, operating systems, and device types, and how recognition holds up as platforms tighten their privacy controls.
Reporting directly to the Head of Digital Intelligence Products, you will work at the intersection of device intelligence, data science, and massive-scale engineering. You won't just be writing tickets; you will be deep in the data, writing your own queries, building prototypes, and testing hypotheses before the team commits to building.
This role is open to current product managers and to experienced engineers who want to branch out into product. If you have built device fingerprinting or tracking technology, are comfortable debating methods and trade-offs with engineers & data scientists, and measure your work by outcomes, we want to hear from you.
Own the Device Recognition Roadmap: Drive the end-to-end product lifecycle for Device Recognition and the Global Device ID, improving recognition accuracy, persistence over time, and linking of devices across customers. You will own priorities, scope, and release trade-offs.
Define Signal Collection: Partner with Engineering to define, prioritize, and deliver signal collection across our Web, iOS, and Android SDKs. You will own the trade-offs between signal richness, SDK footprint, performance, and privacy on each platform.
Navigate Platform Nuances: Track and respond to changes across browsers, operating systems, and device types, including privacy features such as tracking prevention, storage partitioning, fingerprinting protections, and app tracking restrictions that affect recognition.
Get Your Hands Dirty: Write your own SQL, analyze signal stability and distributions, and build prototypes to validate ideas before engineering invests in them.
Data Science Partnership: Work hand-in-hand with Data Scientists on the matching and linking logic behind device recognition. Together with Data Science and Engineering, you will define acceptance criteria for recognition performance (e.g., match rate, false merge and false split rates) and track them in production.
Continuous Discovery & Experimentation: Utilize prototyping and experimentation to de-risk solutions before building. You will validate hypotheses about signal stability, spoofing, emulators, and anti-detect browsers through data analysis and pilot programs.
Customer Evaluation: Define how customers evaluate and calibrate Device Recognition, including POCs against competitors.
Cross-Suite Integration: Engage with internal product teams to ensure Device Recognition integrates seamlessly with Behavioral Analytics, the broader Digital Intelligence suite, and other Socure Products (RiskOS, Document Verification, etc…) to provide a unified risk score to our clients.
Go-to-Market Strategy: Partner with Product Marketing and Sales to help drive adoption and usage, create technical documentation, and evangelize the product to clients in Fintech, E-commerce, and Gaming.
Support Wider Digital Intelligence Initiatives: Provide product expertise and support for adjacent Digital Intelligence products and critical initiatives, ensuring resource alignment with the highest company priorities.
Experience: 5+ years of Product Management or Software Engineering experience, with at least 2+ years in a highly technical domain (Device Intelligence, Fraud Prevention, Identity, Cybersecurity, or AdTech). Engineers moving into product are welcome; tell us about the products you shaped.
Device Fingerprinting & Tracking: Hands-on experience building or managing device fingerprinting, device recognition, or tracking technology. You understand how browser, hardware, and network attributes combine into a device identifier, and where each one breaks down.
SDK & Platform Depth: You understand data collection through JavaScript and native SDKs, and the nuances between web, iOS, and Android, as well as across browsers and device types. You know what changes when a user goes incognito, clears storage, updates an OS, or runs an emulator or anti-detect browser.
Hands-On Technical Fluency: You are proficient in SQL and comfortable performing your own data analysis to answer questions without waiting for an analyst. You can build working prototypes in Python or a similar language. You understand API design (REST/JSON) and the basics of machine learning pipelines.
Outcome Over Output: You are goal oriented and focus on moving business metrics (e.g., "Increase cross-customer device recognition by 20%") rather than just shipping features. You are familiar with setting and tracking KPIs like match rates, False Positive Rates, and Fraud Detection Rates.
Problem Solving: You can partner with engineering and data science to break down complex, ambiguous problems, like "how do we recognize a returning device after its browser storage has been cleared?", into shippable iterations.
AI Fluency: You use AI tools in your daily work, including data analysis with Data Science, prototyping, and reporting.
Communication: You communicate clearly and concisely, in writing and in person, with engineers, data scientists, customers, and executives.
Device-Focused Company Experience: Prior experience at iovation, Sardine, Fingerprint, ThreatMetrix, IPQS, or other device-focused companies.
Device Integrity & Attestation: Familiarity with hardware-backed and platform signals such as Apple App Attest, DeviceCheck, and Google Play Integrity.
Graph & Entity Resolution: Experience linking entities (devices, users, accounts) across large datasets, including identity graphs.
Regulatory Knowledge: Understanding of privacy landscapes regarding device data and tracking (GDPR, ePrivacy, CCPA) and how consent and retention requirements influence product architecture.
Network Intelligence: Experience with IP, proxy, VPN, and carrier signals and how they complement device recognition.
Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly.
Follow Us!
YouTube | LinkedIn | X (Twitter) | Facebook
