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Lead Site Reliability Engineer

EPAM Systems

Remote
Remote Senior 🇬🇧 English
Python AWS GCP Azure SLO/SLI Error budgets Postmortems Capacity planning Incident management Monitoring tools CI/CD Infrastructure as Code Configuration management Kubernetes Docker Generative AI AIOps

Job description

About the role

We are looking for a highly skilled Lead Site Reliability Engineer to drive reliability, scalability, and efficiency across our systems. You will work closely with development, security, quality, and operations teams to embed SRE practices and deliver seamless user experiences.

Key responsibilities

  • Collaborate with cross‑functional teams to define and enforce Service Level Objectives (SLOs) and error budgets.
  • Design, implement, and maintain cloud‑based solutions on AWS, GCP or Azure.
  • Automate infrastructure provisioning, monitoring, and incident response using CI/CD pipelines and Infrastructure‑as‑Code tools.
  • Lead the adoption of AI‑enabled platform capabilities such as generative AI, autonomous agents, and AIOps.
  • Conduct post‑mortems, capacity planning, and continuous improvement to reduce operational toil.
  • Mentor junior engineers and promote best practices in reliability engineering.

Required profile

  • Bachelor’s degree in Computer Science, Engineering or a related field.
  • 5+ years of hands‑on experience in Site Reliability Engineering or a closely related role.
  • Proven experience managing production services in a public cloud environment (AWS, GCP, or Azure).
  • Strong communication skills in English (Upper‑Intermediate level or higher).

Required skills

  • Python or comparable scripting/programming language.
  • Deep knowledge of SRE practices: SLO/SLI, error budgets, post‑mortems, capacity planning, incident management, and toil reduction.
  • Expertise with monitoring tools and alerting systems.
  • Proficiency in CI/CD tools, Infrastructure‑as‑Code, and configuration management.
  • Solid experience with container orchestration (Kubernetes, Docker).
  • Familiarity with AI/ML operational concepts (GenAI, AIOps, LLM deployment).

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EPAM Systems