[Hiring] Engineering Manager, Smart Signals @Fingerprint

Role Description

Fingerprint's Smart Signals team is the front line of our fraud and device intelligence capabilities. We produce the signals — Bot Detection, Browser tampering detection, Incognito Detection, suspect score, fraud score and much more — that developers use to build secure, fraud-resistant applications. As the fraud landscape shifts toward agentic AI attacks and telemetry tampering, this team's work has never been more strategically critical. Smart Signals is key to Fingerprint's primary product differentiation - Every new signal you ship directly impacts ARR.

We are hiring a Smart Signals Engineering Manager to own the day-to-day execution, people leadership, and technical delivery of the Smart Signals team.

What You’ll Do

• Lead the team.
  • Own 1:1s, performance calibrations, career development, and hiring.
  • Set the bar for code quality, on-call discipline, and delivery.
  • Coach intentionally — especially engineers approaching Staff.
• Drive execution.
  • Own sprint planning and roadmap delivery.
  • Manage scope, urgency, and quality tradeoffs — know when to ship and when to slow down.
  • Run tight processes: planning, incident response, on-call rotations, postmortems.
• Stay technically grounded.
  • Maintain enough depth in the signals stack to review designs, challenge architectural decisions, and surface risks before they become incidents.
  • Partner with ML Engineers on signal pipelines and model deployment.
• Coordinate across teams.
  • Represent Smart Signals in technical discussions across Engineering.
  • Manage cross-team dependencies proactively and communicate tradeoffs clearly to PMs and leadership.
• Shape signal strategy.
  • Partner with Eng Leadership and Product on roadmap prioritization.
  • Translate research findings into executable engineering plans.
  • Contribute to detection strategy as the threat landscape evolves.

Qualifications

• Engineering management experience: 4+ years managing a team of 8–10 engineers.
• Technical depth in backend systems: Experience building or operating production backend services at scale.
• Delivery track record: Concrete examples of quarters where your team shipped reliably.
• Cross-functional collaboration: Direct experience working with PMs and research or data partners.

Requirements

• Fraud detection or security signals familiarity: Some exposure to fraud, risk, or device intelligence systems.
• ML-in-production exposure: Experience working alongside ML engineers or data scientists.
• High-growth B2B SaaS or API-first company experience.
• Real-time or latency-sensitive systems: Experience managing engineers working on signal pipelines or edge computation.

Compensation Range

For US-based employees, the cash compensation range for this role is $159,000 – $215,000. 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, we share salary ranges on all job postings.

Offers vary depending on relevant experience, education, certifications/licenses, skills, training, and market conditions.

Benefits

• Dedicated to creating an inclusive work environment for everyone.
• Embrace and celebrate the unique experiences, perspectives, and cultural backgrounds of each employee.
• Foster an environment where employees feel respected, valued, and empowered.
• Encourage applications from underrepresented groups in tech.