Staff+ Software Engineer, Capacity Engineering

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest is seeking a Staff Software Engineer, Capacity Engineering. The team is responsible for efficiently managing one of the largest-scale cloud-native infrastructures in the world. This role is highly impactful, as efficiency is an ongoing strategic priority for Pinterest. The role has direct visibility across Pinterest Engineering and with Engineering and company leadership. The team is looking for a candidate with a strong background in implementing performance and efficiency projects on large scale distributed systems. In this individual-contributor role you will own and drive performance and efficiency for a core area of Capacity Engineering, partnering with the company-wide efficiency lead and collaborating with performance and efficiency leaders across the organization. What you’ll do: Drive efficiency in large-scale shared environme

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

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 y

Why Harvey At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. Role Overview Harvey is building the AI platform trusted by the world’s leading law firms and enterprises. Our infrastructure is the foundation that powers every customer interaction, every model inference, and every production workload. We’re looking for a Production Engineer to help build and operate Harvey’s core compute and networking infrastructure, Kubernetes platform, workflow orchestration platform, and production infrastructure foundations. You’ll work on the systems that enable engineering teams to move quickly and operate reliable services at scale. In this role, you’ll improve the reliability, scalability, security, and efficiency of Harvey’s infrastructure platform. You’ll solve complex production challenges across compute fleet management, capacity planning, infrastruc

Why Harvey At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. Role Overview Harvey is building the AI platform trusted by the world’s leading law firms and enterprises. Our infrastructure is the foundation that powers every customer interaction, every model inference, and every production workload. We’re looking for a Production Engineer to help build and operate Harvey’s core compute and networking infrastructure, Kubernetes platform, workflow orchestration platform, and production infrastructure foundations. You’ll work on the systems that enable engineering teams to move quickly and operate reliable services at scale. In this role, you’ll improve the reliability, scalability, security, and efficiency of Harvey’s infrastructure platform. You’ll solve complex production challenges across compute fleet management, capacity planning, infrastruc

About the Role REMOTE IN INDIA We're looking for a software engineer to build the Kubernetes-native control plane that provisions and runs our GPU inference fleet. You'll design a manifest-driven API where the inference team declares what they need, whether that's a cluster, a model deployment, or a capacity change, and our controllers handle the reconciliation, provider/runtime selection, and lifecycle management underneath, so the inference team never has to know or care which specific serving stack, scheduler, or hardware pool is doing the work. You'll also build the systems that keep the fleet efficient, not just running, including defragmentation and rebalancing logic that consolidates scattered workloads back into contiguous capacity, and scheduling/bin-packing improvements that push GPU utilization up without hurting latency. The core value we're after is decoupling the people building on top of the platform from the operational and runtime complexity underneath, while squeezing more usable capacity out of the same hardware. You'll build the controllers, reconciliation loops, and self-service surface (API/CLI, not tickets) that make that decoupling real, plus the event-driven health, remediation, and utilization systems that keep it running and efficient without a human in the loop. Strong candidates have hands-on experience with Kubernetes controller/CRD patterns, have built or operated a platform API that abstracts multiple backends behind one interface, understand GPU scheduling and capacity efficiency (fragmentation, bin-packing, right-sizing), and think about GPU infrastructure as software to be engineered. A product mindset - you've built internal platforms or APIs consumed by other engineering teams and care about the developer experience of what you ship. You build it, you own it. You are not only responsible for delivering the software but also for operating and supporting it in production. Responsibilities Build the provisioning state machine