Job description
Upwork ($UPWK) is the world’s work marketplace. We serve everyone from one-person startups to over 30% of the Fortune 100 with a powerful, trust-driven platform that enables companies and talent to work together in new ways that unlock their potential. Last year, more than $3.8 billion of work was done through Upwork by skilled professionals who are gaining more control by finding work they are passionate about and innovating their careers.
This is an engagement through Upwork’s Hybrid Workforce Solutions (HWS) Team. Our Hybrid Workforce Solutions Team is a global group of professionals that support Upwork’s business. Our HWS team members are located all over the world. This is an opportunity to work with a major revenue-producing website with millions of users. In addition to making sure everything works you are also expected to contribute to the continuous improvement of our environment. This is a full time position (~40 hours per week, Monday-Friday). This role will participate in our production on-call rotation in your day-time and on some weekends (once every 2-3 weeks).
Work/Project Scope:
- Serve as a technical leader in modern SRE practices with a focus on zero-trust infrastructure, platform observability, and cloud-native scalability.
- Guide the architectural evolution of reliability systems, including multi-cluster Kubernetes environments, GitOps workflows, and service mesh integration.
- Champion SLO-driven engineering across teams and establish frameworks for defining, tracking, and enforcing reliability standards.
- Partner with platform and security teams to enable service-to-service authentication, policy enforcement, and resilient control planes.
- Develop AI-assisted tools and workflows (e.g., for incident triage, RCA generation, auto-remediation) to reduce operational burden and accelerate resolution.
- Define and maintain end-to-end observability strategies including distributed tracing, metrics pipelines, and log enrichment.
- Drive infrastructure automation efforts using IaC best practices, with an emphasis on policy-as-code, workload identity, and platform governance.
- Lead post-incident reviews and reliability audits to surface systemic gaps and drive continuous improvement.
- Mentor engineers across infrastructure and application teams on designing and operating reliable, scalable systems.
Must Haves (Required Skills):
- 10+ years in SRE, DevOps, or production engineering roles, including experience operating large-scale distributed systems in production
- Deep expertise in Kubernetes operations, including multi-cluster orchestration, service mesh (Istio or equivalent), and workload policy management (e.g., OPA, Kyverno)
- Proven experience building and maintaining GitOps pipelines using tools like ArgoCD or Flux
- Strong fluency in observability tooling (e.g., Prometheus, OpenTelemetry, Grafana, or Datadog), with a focus on SLO-based alerting and incident detection
- Familiarity with reliability-as-code practices and automation using scripting languages (Python, Go, or Bash) and AI-enhanced workflows (e.g., Cursor, incident bots, PR-generating agents)
- Experience designing and enforcing zero trust service-to-service authentication, workload identity, and mTLS policies
- Track record of leading incident review programs, standardizing postmortems, and driving systemic reliability improvements
- Ability to work cross-functionally with platform, security, and developer enablement teams to embed resilience across the SDLC.
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