Forward Deployment Engineer (SRE)

PwC Acceleration Centers; Bengaluru; On-site; INR 400,000 - 700,000; Full time

Job summary

PwC Acceleration Centers in Bengaluru seeks a senior, customer-facing Site Reliability Engineer who owns the reliability of a client's production systems end to end. Embedded as the main technical contact, you will design reliable infrastructure, lead incidents, and mentor the team.

You will apply AI-assisted operations, define SLIs/SLOs, manage observability, and collaborate with product and engineering teams to share learnings and improve overall resilience.

Qualifications

• Extensive SRE experience with ownership of production reliability on AWS.
• Experience running Kubernetes and AWS services at scale.
• Track record defining SLIs/SLOs and error budgets.
• Strong observability practice.
• Incident leadership and post-mortem facilitation.
• Automation skills in Python, Go, or Bash.
• AWS Associate level certification minimum.

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

AWS & SRE ownership

Incident leadership

Automation (Python/Go/Bash)

Tools

Kubernetes

Prometheus/Grafana

Terraform

GitOps (ArgoCD)

Helm

PagerDuty/Opsgenie

Job description

Site Reliability Engineering | Forward Deployed Engineering

Experience Required

6–9 years.

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
• Mentors and raises standards across the team.