Senior Golang Engineer

Zendesk Zendesk · Enterprise · Krakow, Poland

Senior Software Engineer for Zendesk's Workforce Management product team, focusing on building and scaling AI-powered backend systems for forecasting, scheduling, and agent performance tracking. The role involves full SDLC ownership, collaboration, code quality, technical debt reduction, and mentorship.

What you'd actually do

  1. Design, implement, test, and maintain backend services in Go that power Workforce Management features used by customers at scale.
  2. Own components through the full SDLC: participate in discovery, estimate and plan work, deliver features, and support them in production.
  3. Collaborate closely with product managers, SREs, QA, and other engineers to translate requirements into reliable, maintainable solutions.
  4. Write clear, well-tested code and perform thoughtful code reviews that raise team quality and share knowledge.
  5. Help identify and reduce technical debt by breaking complex problems into manageable tasks and proposing pragmatic improvements.

Skills

Required

  • 5+ years professional software engineering experience
  • 3+ years building backend services (microservices/distributed systems)
  • Strong proficiency in Go (Golang)
  • Go testing practices
  • containerized development using Docker
  • Solid experience with relational databases (PostgreSQL or MySQL)
  • designing efficient data access patterns
  • Practical cloud experience (AWS preferred)
  • familiarity with CI/CD pipelines
  • infrastructure-as-code concepts
  • Working knowledge of distributed systems concepts
  • patterns for reliable services
  • Experience with event-driven architectures
  • message systems (Kafka or similar)
  • designing robust REST APIs and integrations
  • Excellent communication skills
  • collaborative mindset
  • focus on mentorship
  • continuous improvement

Nice to have

  • Experience with PHP/Laravel
  • working alongside PHP-based services
  • Familiarity with analytical databases such as ClickHouse
  • Experience with observability and error-tracking tools (Datadog, Sentry)
  • proactive monitoring practices
  • Exposure to CI/CD tooling and orchestration (GitHub Actions, Jenkins, Spinnaker, Kubernetes)

What the JD emphasized

  • AI-powered solution
  • automation
  • intelligent customer experiences
  • data-driven automation
  • optimize workforce efficiency