Site Reliability Engineer_ AWS certified

PwC Acceleration Center India; Bengaluru; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

PwC Acceleration Center India is seeking a senior Site Reliability Engineer to own the reliability of a client's production systems end to end on AWS. Embedded as the main technical point of contact, you will design reliable infrastructure, lead incidents, and mentor the team.

The role emphasizes defining SLIs and SLOs, AI-assisted operations, and blameless post-mortems to improve stability. You will lead the on-call rotation and guide customers on reliability while collaborating with product

Qualifications

• Substantial SRE experience with ownership of production reliability on AWS.
• Experience running Kubernetes and AWS services at scale.
• Strong observability and incident leadership experience.
• Hands-on automation skills with Python, Go, or Bash.
• Experience introducing AI SRE tooling and guardrails.

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.

Skills

SRE ownership

Incident leadership

Python/Go/Bash

AWS experience

Kubernetes experience

Observability

Tools

Prometheus

Grafana

Datadog

OpenTelemetry

PagerDuty

ArgoCD

Terraform

Job description

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

Experience 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

• 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