Software Engineer

Role & responsibilities

Role & responsibilities Greetings from Pwc!Role- Site Reliability Engineering ( Mandatory skills AWS, AI & SLI OR SLO)Location- Hyderabad & BangaloreExperience Required -6-8years
If interested Share cv on [email removed] or WhatsApp on [phone removed] with below detailsTotal experience-Relevant Experience-Current location-Preferred location-Current CTC-Expected CTC
Job SummaryA 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