Prelude
Founding Device Fingerprinting Engineer
2mo ago
EuropeSeniorRemoteotpsmsfraud-detectionbackend
Founding engineer role focused on device fingerprinting, part of a platform for user authentication and onboarding.
Responsibilities
- Fingerprinting is becoming a first-class pillar of Prelude's fraud detection engine — and this is the founding role that will define it. You will own the entire fingerprinting surface: architecture, research, production systems, and eventually the team we build around you. You'll report directly to leadership and shape the roadmap from scratch.
- Fraud is an adversarial game. Attackers use emulators, residential proxies, VPNs, device spoofing, and anti-detect tooling to flood our customers' authentication pipelines with fake traffic. Your job is to make that invisible — or at least expensive enough not to be worth it.
- You'll build the systems that collect, process, and exploit device and network signals at scale: from raw hardware attributes and TLS fingerprints to IP risk scoring and carrier intelligence. You'll combine classical feature engineering with ML to produce high-fidelity risk signals that feed our real-time scoring engine — processing millions of authentication attempts per day in milliseconds.
- This role sits at the intersection of security research, systems engineering, and applied machine learning. It's for someone who thinks like an attacker, builds like an engineer, and reasons like a data scientist.
- Owning the fingerprinting roadmap end to end — from signal collection in our mobile SDKs (iOS, Android) and server-side APIs, to the feature engineering pipelines that turn raw attributes into fraud signals
- Building and hardening device fingerprinting systems — persistent device identity across app reinstalls, rooted/emulated device detection, hardware attestation, and spoofing resistance for both web and mobile contexts
- Developing network intelligence signals — IP reputation scoring, proxy/VPN/datacenter detection, TLS/JA4 fingerprinting, carrier and MCCMNC enrichment, and residential vs. commercial traffic classification
- Applying ML to fingerprinting problems — anomaly detection on device attribute distributions, clustering to identify fraud rings sharing infrastructure, supervised classification of suspicious signal patterns, and adversarial robustness against evolving evasion techniques
- Integrating with our real-time scoring engine — producing low-latency features that enrich our per-authentication risk model under strict latency constraints
- Researching attacker techniques — reverse-engineering anti-detect tooling, automation frameworks, and bypass techniques to stay ahead of the adversarial curve
- Laying the groundwork for a team — defining engineering standards, research practices, and data pipelines that will scale as we hire around you.
Requirements
- 5+ years of experience in a relevant field — fraud detection, bot mitigation, mobile security, or detection engineering; you've shipped systems in production, not just research prototypes
- Deep knowledge of device fingerprinting — mobile hardware signals, OS-level attestation (Play Integrity, DeviceCheck, SafetyNet), browser fingerprinting APIs, and spoofing/emulation detection
- Hands-on experience with network intelligence — TLS fingerprinting (JA3/JA4), IP enrichment pipelines, proxy/VPN classification, AS number analysis, and carrier-level signals
- Applied ML experience in a security context — feature engineering, anomaly detection, clustering, and classification with end-to-end ownership from training through production deployment
- An adversarial mindset — you know the attacker landscape (emulators, spoofing techniques, anti-detect browsers, residential proxy networks) and design systems with bypass attempts already in mind
- A preference for simple, robust designs over clever, fragile ones — with strong intuition for what will hold up at scale under active adversarial pressure
- Fluent English, given our international team and customer base
- Nice to have:
- Familiarity with phone/SIM authentication context, GSMA intelligence, or telco APIs
- Experience with JA4 or other network fingerprinting techniques
- Proficiency in Go, Rust, or Python for backend/data work
- Experience with stream processing systems (SQS, Kafka) or OLAP stacks (ClickHouse, Redshift)
- iOS or Android SDK internals knowledge
- Published research, open-source contributions, or technical writing in the fraud/bot detection space.
Conditions
- Today, we're a team of 60 and growing, based in Paris, building products that power secure and high-performance user onboarding for companies across the world. We believe small, highly skilled teams outperform large, fragmented organizations, and we are intentional about staying focused on impact, quality, and speed.
- We operate with a flat org structure and value in-person collaboration, which helps ideas move faster, decisions stay grounded, and teams take full ownership of what they build. Our values
- Care We care deeply about our customers, our teammates, and the quality and reliability of what we ship.
- Bias for Action We move fast, test in the real world, and iterate quickly rather than over-optimizing in theory.
- Ownership We take responsibility end to end, from identifying problems to delivering outcomes and learning from results.
- Competitive compensation package with BSPCEs
- Flexible remote policy
- 100% travel to the office subsidised
- Health insurance via Alan
- Urban Sports Club gym membership
- We will provide you with the gear you need for your role (a laptop and a phone, for on-call rotations)
- Swile meal vouchers
- Free snacks and drinks in the office
- An annual offsite in a great location (last one was at La Pradet!)
- The opportunity to build something from 0-1, and make an impact every day
Other
- Prelude is redefining how companies authenticate and onboard users - turning what's traditionally a cost center into a growth lever.
- Our flagship product lets businesses send OTP codes with the best price-to-conversion ratio on the market, dynamically selecting the most effective channel in real time (optimized SMS, WhatsApp, and more) while actively blocking spam and fraud that legacy providers miss.
- Founded in 2022 by former Zenly team members who lived the pain of broken SMS authentication firsthand, we're already serving fast-growing companies across Europe and are expanding into the US.
- But authentication is only the starting point - we're building the platform for trust at scale, with an ambitious roadmap of market-defining products ahead.