Drimva

Zscaler

Staff Software Development Engineer (Microservices)

$133K–$190K

Santa Clara, California, USA · Staff · Full-time · Posted Oct 8, 2026

Experience
5+ years in software development, including 2+ years building and operating production microservices.

About the job

Build, operate, and improve domain-aligned microservices for the Zscaler Internet Access control plane, owning services from design through deployment.

What you'll do

  • Develop low-latency, event-driven microservices and contribute to resilience and multi-region readiness.
  • Establish service development, CI/CD, testing, observability, and safe delivery practices; participate in incident response and on-call rotations.
  • Collaborate on designs and service security, and improve performance, capacity planning, autoscaling, and cloud costs.

What they ask for

  • 5+ years in software development, including 2+ years building and operating production microservices; proficiency in Go and solid software engineering fundamentals.
  • Kubernetes experience, strong Docker fundamentals, AWS service delivery, and familiarity with Git-based workflows, CI/CD, autoscaling, and rollout patterns.
  • Messaging and data-store experience with Kafka or a similar broker, strong SQL proficiency, and experience with at least one NoSQL store.
  • Observability across metrics, logs, and distributed tracing; incident management experience; working knowledge of OAuth2/OIDC, mTLS, and secrets management.

Nice to have

  • Hands-on GitOps, feature flags, and progressive delivery; familiarity with service mesh and policy-driven traffic management.
  • Experience with chaos engineering, multi-region patterns, migrations, performance profiling, or AWS cost optimization.

Pay

$133,000 — $190,000 USD (base salary)

Tools

Go, Kubernetes, Docker, AWS, Kafka, PostgreSQL, MySQL, Amazon RDS

AI focus

Foundational understanding of AI/ML technologies and experience leveraging, securing, or positioning AI-driven solutions to optimize outcomes; preferred ability to use AI technologies and workflows to improve operational efficiency.

Model-written summary · the original posting is authoritative

First seen Oct 10, 2026 · Last verified Nov 4, 2026 (UTC)