Staff Software Engineer

Title: Staff Site Reliability Engineer, Cloud Cost & Engineering Efficiency Location: Noida / Bangalore (Hybrid) Summary of role Sumo Logic's microservices architecture, hosted on AWS, ingests petabytes of data daily across many geographic regions in support of our planet-scale observability and security products, serving hundreds of millions of queries a day against thousands of petabytes of data. At that scale, every inefficiency — in code, architecture, or infrastructure — compounds into real cost. This role sits within the Product SRE organization, working alongside your global SRE team on your product area's reliability roadmap — with a mandate that leads with code as much as operations. You'll find where Sumo's systems are spending more compute, storage, or engineering time than necessary, and fix it in the code and architecture, not just the infra config, while also carrying the fuller SRE mandate — reliability, security posture, and improving the day-to-day experience of the engineers within your product area. You'll be part of a team that blends SRE and backend software engineering skillsets, partnering closely with product engineering teams across your product area. This is an engineering role — the work is about shipping code, architecture, and system-level changes that improve unit economics, not managing cost dashboards, tagging, or reserved-instance/savings-plan purchasing. What you’ll do Continuously discover cost and efficiency opportunities through production profiling, telemetry, cost data, capacity trends, and system-level analysis — across algorithmic inefficiencies, resource-heavy code paths, and architectural decisions — and turn ambiguous problems into prioritized engineering initiatives. Apply performance and capacity engineering techniques to understand CPU, memory, storage, network, and I/O behavior under real production workloads, and optimize the resulting resource footprint. Write production-grade code to implement the optimizations you identify — JVM/GC tuning, algorithmic and resource-efficiency improvements, re-architecting inefficient services — in systems that process petabytes of data daily. Define and track engineering efficiency metrics such as cost per GB ingested, cost per query, cost per event, resource utilization, or cost per customer workload, and translate the work into measurable impact for engineering and business stakeholders. Lead complex, cross-team engineering initiatives from problem discovery through design, implementation, rollout, and measurement — influencing teams where you don't have direct ownership — and help establish engineering patterns and practices that make cost and efficiency a continuous part of the development lifecycle. Partner with engineering teams in your product area to prioritize changes, and with developer infrastructure and Global SRE to align with the broader reliability roadmap.