





Senior staff-level SRE in Bengaluru with notable brand and multi-cloud requirements yields moderate applicant density.
Core SRE skills transfer across industries, but GCP data/AI and agentic-AI expertise moderately increases domain specificity.
Explicit 9+ years, master's, GCP/IaC/SLOs and staff leadership make hiring filters highly stringent.
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Own and enhance reliability, scalability, and operability of enterprise data and AI platforms using Google Cloud Platform and multi-cloud (GCP, Azure).
Define and enforce SLOs/SLIs/error budgets, drive incident management improvements, and lead blameless post-mortems to eliminate systemic reliability issues.
Lead multi-cloud platform architecture decisions, automate infrastructure and workflows with Terraform, Helm, GitOps, and implement self-healing, auto-scaling infrastructure patterns.
Master's degree in Computer Science, Engineering, or related field, or equivalent practical experience.
9+ years of experience in Site Reliability Engineering, DevOps, or Platform Engineering in large-scale production environments.
Deep hands-on expertise with GCP services including GKE, Cloud Run, BigQuery, Pub/Sub, GCS, Composer, Dataflow, Vertex AI and Infrastructure-as-Code tools like Terraform, Helm plus GitOps workflows (ArgoCD, Flux).
Experience with multi-cloud environments (GCP and Azure) including cross-cloud networking, identity federation, and cost governance.
Experienced technical leader with history of influencing cross-functional engineering teams and driving organizational reliability improvements without direct authority.
Strong proficiency in SRE practices including defining and operating against SLOs/SLIs/error budgets, observability tooling, incident response, and automation tooling in a complex cloud-based data platform environment.
Expertise in architecting and optimizing large-scale, multi-cloud data and AI platforms including agentic AI systems, with understanding of data security, governance, and operational challenges in retail or e-commerce contexts.