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Hims & Hers, a public healthcare platform (NYSE: HIMS), is seeking a Senior Reliability Engineer to own and measurably improve system reliability across their customer-facing health and wellness platform. This role focuses on building observability, tooling, and automation that detect and prevent issues before they impact customers.
Key responsibilities include:
- Own reliability for Tier 1 customer journeys (checkout, telehealth visits, prescription fulfillment) by defining and instrumenting SLOs, golden signals, and business-level monitors. Track the ratio of system-detected vs. human-detected degradation and drive improvement.
- Lead capacity and resilience engineering for high-stakes seasonal events and steady-state growth: design load tests, analyze prior event performance second-by-second, investigate database and backend bottlenecks, and harden systems across caching, GraphQL, VPC capacity, and vendor rate limits.
- Mature incident response infrastructure by connecting FireHydrant, Datadog, and Jira into an automated pipeline: automated incident and RCA ticket creation, SLO burn-rate alerting with deduplication, Tier 1 alert routing, and enforced post-mortem action tracking. Author and maintain runbooks and severity standards.
- Build and operate AI agents and tooling to reduce manual operational work: OER report generation, RCA drafting, stale action-item detection, monitor and runbook gap detection, and automated incident triage. Ship these as reusable capabilities.
- Serve as the deep-debugging expert for cross-boundary issues (silent service-to-service failures, anomalous traffic, multi-layer regressions). Turn learnings into runbooks and tooling so teams can resolve similar issues independently.
- Maintain tooling that powers bi-weekly VP-level Operational Excellence reviews and monthly cross-engineering OER metrics. Drive resulting action items to closure.
- Raise the bar across engineering by documenting work, onboarding teammates, and coaching engineers on SLOs, blameless post-mortems, and on-call practices.
The company emphasizes AI-first practices: every engineer receives a Claude Enterprise license and is expected to use AI as a core part of investigation, building, and writing.
REQUIREMENTS:
- 5+ years as a Software, SRE, Platform, or Infrastructure Engineer with a track record of owning reliability outcomes for production systems customers depend on
- Strong software engineering fundamentals; solve reliability problems by writing code and building tooling; comfortable reading application code across the stack
- Hands-on depth in observability and SLO engineering: golden signals, burn-rate alerting, journey-level monitors, alert deduplication (Datadog preferred; Prometheus/Grafana and OpenTelemetry welcome)
- Production experience with AWS, Kubernetes/EKS, Terraform, and PostgreSQL (RDS/Aurora)
- Experience running or maturing incident management end-to-end: on-call design, escalation policies, incident command, blameless post-mortems, action-item follow-through in FireHydrant or PagerDuty
- Daily, practical use of AI coding and analysis tools (Claude, Cursor, or similar) to accelerate investigation, code, documentation, and reporting; clear judgment about when to trust output and when to verify
- Communication skills to explain risk, tradeoffs, and post-incident learnings to engineers and leadership in writing and review meetings
PREFERRED QUALIFICATIONS:
- Experience building AI agents or LLM-backed automation for operations: incident triage, RCA generation, alert correlation, observability data analysis, ideally with MCP or tool-calling integrations against Datadog, FireHydrant, or Jira
- Load-testing and performance-engineering experience at meaningful scale (k6 or similar), including validating systems well above expected peak
- Familiarity with service mesh (Istio) and its observability and traffic-management features
- Background in regulated or healthcare environment where reliability and data handling carry patient-safety and compliance weight
- Experience designing vendor and partner escalation frameworks with defined severities and response SLAs
