Site Reliability Engineer_ Certified_ Senior Associate

PwC

Hyderabad, Bengaluru

In loco

INR 2.500.000 - 4.000.000

Tempo pieno

3 giorni fa
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Descrizione del lavoro

PwC is seeking a senior Site Reliability Engineer to own the reliability of client production systems end to end. You will design reliable infrastructure, lead incidents, apply AI-assisted operations, and mentor the team.

You will manage SLIs/SLOs, operate Kubernetes clusters on AWS, and contribute to blameless post-mortems while guiding customers on best reliability practices.

Competenze

  • Substantial SRE experience with real ownership of production reliability on AWS.
  • Experience running Kubernetes and AWS services at scale.
  • A track record of defining and managing SLIs, SLOs, and error budgets.
  • Strong observability practice and incident leadership.

Mansioni

  • Own the reliability of production systems for one or more enterprise customers on AWS.
  • Define and manage SLIs, SLOs, and error budgets, ensuring meaningful monitoring.
  • Lead response to serious incidents and conduct blameless post-mortems.
  • Operate and optimise Kubernetes clusters and AWS services as workloads grow.
  • Introduce AI SRE tooling to speed up triage and resolution with guardrails.
  • Mentor associate engineers and share field learnings with teams.

Conoscenze

AWS expertise
Kubernetes
Observability
SLIs/SLOs
Incident leadership
AI-assisted operations
Automation (Python/Go/Bash)

Formazione

AWS Associate Certification

Strumenti

Docker
Kubernetes (EKS)
Helm
Terraform modules
GitOps (ArgoCD)
PagerDuty

Descrizione del lavoro

Role & responsibilities

Greetings from Pwc!Role- Site Reliability Engineering ( Mandatory skills AWS, AI & SLI OR SLO)

Location- Hyderabad & BangaloreExperience

Required -6-8years

Job Summary

A senior, customer-facing SRE who owns the reliability of a client's production systems end to end. Embedded as the main technical point of contact, you will design reliable infrastructure, lead incidents, apply AI-assisted operations, and mentor the team.

Key Responsibilities
  • Own the reliability of production systems for one or more enterprise customers on AWS.
  • Define and manage SLIs, SLOs, and error budgets, and ensure monitoring provides meaningful insight.
  • Lead the response to serious (P0/P1) incidents and run blameless post-mortems that lead to fixes.
  • Lead within the on-call rotation.
  • Operate and optimise Kubernetes clusters and AWS services as workloads grow.
  • Introduce AI SRE tooling and AIOps where it speeds up triage and resolution, with appropriate guardrails.
  • Advise customers on improving their reliability practices, and mentor associate engineers.
  • Share field learnings with product and engineering teams.
Required Qualifications
  • Substantial SRE experience with real ownership of production reliability on AWS.
  • Experience running Kubernetes and AWS services at scale.
  • A track record of defining and managing SLIs, SLOs, and error budgets.
  • Strong observability practice.
  • Proven incident leadership and post-mortem facilitation.
  • Strong automation skills (Python, Go, or Bash).
  • Hands-on understanding of AI-assisted operations, including introducing AI SRE tooling with sensible guardrails.
  • AWS certification at Associate level as a minimum.
Preferred Qualifications
  • Owning CI/CD pipelines and release automation.
  • Writing and maintaining Terraform modules.
  • GitOps workflows and Helm.
  • Designing telemetry collection across services.
  • Incident-management tooling such as PagerDuty.
  • Hands-on experience integrating AIOps or AI SRE tooling into production operations.
  • Familiarity with observability or evaluation of AI systems (e.g., Langfuse).
  • Experience delivering AI-based work or AI/ML-driven initiatives in production.
  • AWS Certified Solutions Architect Professional and/or AWS Certified DevOps Engineer Professional.
Technical Skills & Tools
  • Cloud (AWS): EC2, EKS, ECS, Lambda, S3, RDS, VPC, IAM, CloudWatch, ELB/ALB, Route 53
  • Containers & orchestration: Docker, Kubernetes (EKS), Helm
  • Observability & monitoring: Prometheus, Grafana, Datadog, OpenTelemetry, Loki, Tempo/Jaeger (tracing), ELK/Elastic
  • Reliability practices: SLIs/SLOs, error budgets, incident command, capacity planning, failure-mode analysis
  • Incident & on-call: PagerDuty, Opsgenie, blameless post-mortems
  • Automation & scripting: Python, Go, Bash, Git
  • AI-assisted operations: AI SRE tooling, AIOps, anomaly detection, automated RCA
  • DevOps (good to have): CI/CD (GitHub Actions, GitLab CI), Terraform modules, GitOps (ArgoCD), Helm
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