Site Reliability Engineer | Senior
Remote, PolskaEPAM
Wynagrodzenie do ustalenia
Wymagania
Bachelor’s degree in Computer Science, Engineering, or a related field
3+ years of hands-on experience in Site Reliability Engineering or related roles
Proven experience in any cloud (AWS/GCP/Azure)
Experience with implementing SRE practices such as SLO/SLI, Error budgets, Postmortems, Reducing Toil, capacity planning, and Incident Management
Python or other scripting/programming language
Strong background in monitoring tools
Proficiency in CI/CD tools, infrastructure as code, and configuration management
Solid knowledge of container orchestration technologies (Kubernetes, Docker)
English language proficiency at an Upper-Intermediate level (B2) or higher
Zakres obowiązków
Collaborate with development, security, quality, and operation teams to implement SRE practices and ensure system reliability
Define and support required level of reliability, availability, and performance for services and applications
Design and deliver Cloud-based solutions tailored to client needs
Troubleshoot, mitigate, and support fixing of the infrastructure and application issues in a timely manner
Implement a monitoring system for the infrastructure and application reliability
Communicate technical concepts clearly to both engineering teams and management stakeholders
Seniority
Senior
Mile widziane
Expertise in deployment and management of LLMs, including technologies like RAG
Certification in Kubernetes, AWS/GCP/Azure, or similar technologies
Proven experience in DevOps
Knowledge of managing and optimizing AI/ML models in production environments, including basic deployment, monitoring, and maintenance
Opis
We are seeking a highly skilled and motivated Site Reliability Engineer (SRE) to join our team. In this critical role, you will collaborate closely with software developers and operations teams to ensure high reliability, scalability, and efficiency of our systems, with a strong focus on meeting and exceeding customer expectations. Your expertise will be crucial in deploying, maintaining, and automating our infrastructure and application environments to ensure seamless user experiences. Your proactive involvement will be key to enhancing system reliability, optimizing resource utilization, and ensuring continuous improvement in our operational practices. Your responsibilities will include defining and tracking Service Level Objectives (SLOs), managing error budgets, and reducing toil through automation. You will play a pivotal role in driving the success of technology initiatives, maximizing their impact across the organization, and ensuring that solutions consistently meet the high standards our customers expect. Responsibilities Collaborate with development, security, quality, and operation teams to implement SRE practices and ensure system reliability Define and support required level of reliability, availability, and performance for services and applications Design and deliver Cloud-based solutions tailored to client needs Troubleshoot, mitigate, and support fixing of the infrastructure and application issues in a timely manner Implement a monitoring system for the infrastructure and application reliability Communicate technical concepts clearly to both engineering teams and management stakeholders Requirements Bachelor’s degree in Computer Science, Engineering, or a related field 3+ years of hands-on experience in Site Reliability Engineering or related roles Proven experience in any cloud (AWS/GCP/Azure) Experience with implementing SRE practices such as SLO/SLI, Error budgets, Postmortems, Reducing Toil, capacity planning, and Incident Management Python or other scripting/programming language Strong background in monitoring tools Proficiency in CI/CD tools, infrastructure as code, and configuration management Solid knowledge of container orchestration technologies (Kubernetes, Docker) English language proficiency at an Upper-Intermediate level (B2) or higher Nice to have Expertise in deployment and management of LLMs, including technologies like RAG Certification in Kubernetes, AWS/GCP/Azure, or similar technologies Proven experience in DevOps Knowledge of managing and optimizing AI/ML models in production environments, including basic deployment, monitoring, and maintenance