Forward Deployment Engineer (SRE)

Job description

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