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Staff Site Reliability Engineer
About this role
Fingerprint seeks its first dedicated Site Reliability Engineer to shape platform reliability across multiple engineering groups. You will work with the Architect, Cloud Platform, and product teams to define and uphold reliability standards, measure performance with SLIs/SLOs, and cultivate an operability mindset. The role reports to the VP of Engineering and requires neutrality across eight engineering groups to ensure consistent reliability practices. The company is 100% remote and serves organisations ranging from startups to large enterprises. Compensation is discussed for US-based employees and depends on experience and location; Fingerprint is remote and does not sponsor visas in many cases.
What you would do
- Define SLIs and SLOs for critical paths with owning teams and ensure visibility and alignment.
- Introduce and coach on error budgets to balance reliability and feature work.
- Own reliability metrics used by leadership to assess progress.
- Strengthen the incident lifecycle including detection, response, postmortems, and follow-ups.
- Improve alert quality, anomaly detection, and escalation design with Cloud Platform collaboration.
- Lead reliability reviews for high-risk changes and new services.
- Introduce deliberate failure testing in staging and production to uncover gaps.
- Embed with teams to transfer knowledge and improve practices.
- Develop reliability leadership in Staff and Lead engineers within groups.
- Codify durable practices like runbooks, on-call standards, and readiness checklists.
What they are asking for
- 10+ years of engineering experience with 3+ years in SRE, production engineering, or reliability-focused Staff role across multiple teams.
- Deep experience designing SLIs/SLOs and driving adoption across product teams.
- Strong incident leadership and experience with high-severity incidents and postmortems.
- Hands-on knowledge of distributed systems failure modes in high-throughput, low-latency environments; fluent with Kubernetes, AWS, and observability tooling.
- Comfort with production coding (Go, TypeScript or similar) and infrastructure as code.
- Proven ability to influence teams without direct management and drive adoption of reliability practices.
- Excellent written communication; able to document incidents, risks, and trade-offs clearly.
- Experience using AI tools in reliability practices and shaping AI-assisted incident response and runbooks.
- Pragmatic approach balancing reliability with delivery; ability to justify investments at the right time.
- Nice to have experience in fraud detection, real-time adversarial domains, multi-region architectures, and scale tooling such as Elasticsearch, Redis, DynamoDB, or Kafka.
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