Forward Deployment Engineer (SRE)

Associate Forward Deployment Engineer (SRE)

Site Reliability Engineering | Forward Deployed Engineering

Location: Bangalore / Hyderabad

Experience Required

3–5 years.

Job Summary

A hands-on, reliability-first engineer embedded within an enterprise client's team. You will help run and stabilise their production systems on AWS, respond to incidents, and use AI-assisted tooling to keep everything healthy day to day.

Key Responsibilities

• Keep production systems reliable for enterprise customers on AWS, and respond quickly when something isn't behaving.
• Own monitoring and alerting, and work to the SLIs, SLOs, and error budgets agreed with customers.
• Handle production incidents (P0–P3) within SLA and take part in the on-call rotation.
• Troubleshoot live issues under pressure, from networking and authentication to container problems.
• Operate and maintain Kubernetes clusters, containers, and core AWS services.
• Use AI SRE assistants and AIOps tooling to detect and resolve incidents faster.
• Automate repetitive operational tasks to reduce manual effort.
• Maintain runbooks and post-incident notes, and collaborate with client engineers over Teams, Slack, and email.

Required Qualifications

• Proven experience keeping production systems reliable on AWS in an SRE or similar role.
• Hands-on experience running Kubernetes and containers in production.
• Working knowledge of core AWS services and cloud-native operations.
• Experience owning monitoring and observability, and working to SLIs, SLOs, and error budgets.
• Experience managing production incidents end to end, including on-call.
• Scripting ability for automation (Python and/or Bash).
• A genuine understanding of how AI-assisted tools support operations, and comfort using them in incident triage and resolution.
• AWS Certified Solutions Architect – Associate (or actively working towards it).

Preferred Qualifications

• Building CI/CD pipelines.
• Infrastructure as Code with Terraform (or equivalent).
• GitOps workflows and Helm.
• Incident-management tooling such as PagerDuty.
• Previous customer-facing experience.
• Hands-on experience with AIOps or AI-driven monitoring and incident tooling.
• Exposure to AI/ML or LLM-based tooling applied to operations.
• Hands-on experience with AI-based work or projects (AI/ML or LLM-powered tools).
• AWS Certified Solutions Architect – Professional 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)
• Observability & monitoring: Prometheus, Grafana, CloudWatch, Loki, OpenTelemetry, ELK/Elastic
• Reliability practices: SLIs/SLOs, error budgets, incident management, performance tuning
• Incident & on-call: PagerDuty, Opsgenie, runbooks, post-mortems
• Automation & scripting: Python, Bash, Git
• AI-assisted operations: AI SRE assistants, AIOps, anomaly detection, alert correlation
• DevOps (good to have): CI/CD (GitHub Actions, GitLab CI, Jenkins), Terraform, Ansible, GitOps (ArgoCD), Helm