Senior SRE Engineer

EPAM Systems; India; Hybrid; INR 1,800,000 - 2,800,000; Full time

Job summary

EPAM Systems is seeking a Senior SRE Engineer to influence design and operational decisions across architecture, engineering, security, and operations teams. The role emphasizes reliability, security, cost, and delivery speed, with onsite presence at the client office three times per week.

Responsibilities include designing observability platforms, managing Datadog-based metrics and alerts, applying SRE principles, collaborating with security teams, and controlling cloud costs while operating

Qualifications

• 6–9 years in SRE, Platform Engineering or related roles.
• Hands-on with AWS services including EKS, EC2, networking and IAM.
• Deep Kubernetes and containerized platforms experience.
• Experience designing and operating observability stacks with Datadog.
• Strong SRE fundamentals: SLOs, error budgets, incident management.
• Cloud security engineering and collaboration with security teams.
• FinOps practices to monitor and control costs of ML/AI services.
• Experience with IaC tools (Terraform, CloudFormation).
• Exposure to multi-cloud or hybrid environments.
• Familiarity with GenAI/Large Language Models workflows.

Responsibilities

• Design and operate observability platforms including monitoring, logging, and alerting.
• Manage metrics, logs, APM, and alerts via Datadog.
• Apply SRE principles: SLOs, error budgets, and incident management.
• Collaborate with security teams to uphold cloud security principles.
• Apply cloud security best practices to ensure system reliability.
• Manage security incidents and drive remediation measures.
• Monitor and optimize costs for ML models and API-based AI services.
• Operate and maintain Kubernetes and containerized platforms.
• Manage AWS infrastructure including EKS, ECS, EC2, networking, IAM.

Skills

AWS

Kubernetes

Datadog

Observability

SRE principles

Security engineering

FinOps

Terraform

CloudFormation

IaC

Multi-cloud

RAG architecture

Generative AI

Tools

Terraform

CloudFormation

Job description

We are seeking a Senior SRE Engineer with strong technical authority to influence design and operational decisions across architecture, engineering, security, and operations teams. The ideal candidate is a pragmatic problem-solver who remains calm and methodical under pressure, balancing reliability, security, cost, and delivery speed while clearly communicating complex technical concepts to diverse audiences. This role requires onsite presence at the client office three times a week.

Responsibilities

• Design and operate observability platforms, including monitoring, logging, and alerting systems
• Manage metrics, logs, APM, and alerting through Datadog
• Apply SRE principles such as SLOs, error budgets, incident management, and reliability engineering
• Collaborate with security teams to uphold cloud security principles
• Apply cloud security best practices to ensure system reliability
• Manage security incidents and drive mitigation and remediation measures
• Monitor, optimize, and control costs associated with ML models and API-based AI services
• Operate and maintain Kubernetes and containerized platforms
• Manage AWS infrastructure, including EKS, ECS, EC2, networking, IAM, and managed services

Requirements

• 6-9 years of hands-on technical experience in SRE, Platform Engineering, Infrastructure, or related roles
• Strong experience with AWS services such as EKS, ECS, EC2, networking, IAM, and managed services
• Deep hands-on experience with Kubernetes and containerized platforms
• Proven experience designing and operating observability platforms, including monitoring, logging, and alerting
• Hands-on experience with Datadog for metrics, logs, APM, and alerting
• Strong understanding of SRE principles, including SLOs, error budgets, incident management, and reliability engineering
• Solid understanding of cloud security principles and experience collaborating with security teams
• Extensive hands-on experience in cloud security engineering, applying best practices to ensure system reliability, managing security incidents, and driving mitigation and remediation measures
• Experience or working knowledge of FinOps practices, including monitoring, optimizing, and controlling costs associated with ML models and API-based AI services
• Nice to have Experience supporting multi-cloud or hybrid environments
• Exposure to Infrastructure as Code, such as Terraform and CloudFormation
• Experience in large-scale, complex, or regulated environments
• Knowledge of vector databases and RAG architecture for building internal SRE knowledge assistants
• Knowledge of Generative AI and LLM platforms, such as Claude and Amazon Bedrock