Staff Software Engineer, Production Engineering

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, infrastructure automation, and production operations. You’ll partner closely with Product Engineering, Security, AI Infrastructure, and Platform teams to ensure our infrastructure scales with Harvey’s rapid growth.

Responsibilities

Design, build, and operate the production infrastructure that powers Harvey’s products and AI workloads; Drive technical direction across compute infrastructure, networking, Kubernetes, workflow orchestration, and production operations; Lead complex, cross-functional technical initiatives that improve reliability, scalability, security, operational efficiency, and infrastructure cost; Partner with Product Engineering, Security, AI Infrastructure, and Platform teams to translate product and business requirements into resilient infrastructure solutions; Establish reusable patterns, tooling, and paved paths that help engineering teams ship and operate production services safely; Raise the engineering bar through thoughtful design reviews, clear technical documentation, operational rigor, and mentorship; Build and operate Harvey’s global compute and network infrastructure, ensuring high availability, scalability, reliability, and performance; Improve compute utilization, performance, and service availability while supporting rapidly growing AI workloads; Develop capacity models, demand forecasts, and fleet lifecycle automation to help infrastructure scale efficiently with business growth; Operate and continuously improve Harvey’s Kubernetes platform, including cluster provisioning, upgrades, networking, monitoring, reliability, performance, and operational automation; Drive infrastructure cost efficiency through capacity management, resource rightsizing, workload optimization, and utilization monitoring; Build secure infrastructure foundations, including identity and access management, network isolation, secrets management, auditing, and compliance controls; Develop scalable Infrastructure-as-Code and automation frameworks using technologies such as Terraform and Pulumi; Improve observability, monitoring, alerting, incident response, and operational readiness across the infrastructure platform; Participate in the on-call rotation, lead incident response when needed, and turn production learnings into durable engineering improvements.

Requirements

10+ years of software, infrastructure, site reliability, or production engineering experience; Deep experience building and operating large-scale cloud infrastructure on AWS, Azure, or Google Cloud Platform; Strong hands-on experience operating Kubernetes in production, including cluster lifecycle management, networking, and reliability; Experience building and operating distributed systems with strong reliability, scalability, and performance characteristics; Experience with infrastructure automation and Infrastructure-as-Code using tools such as Terraform or Pulumi; Strong understanding of compute infrastructure, networking, capacity planning, fleet management, and production operations; Experience designing and operating observability systems, including monitoring, logging, alerting, and incident response; Strong understanding of infrastructure security, including IAM, network security, secrets management, and compliance best practices; A track record of driving complex, cross-functional technical initiatives and influencing engineering decisions without relying on formal authority; Excellent communication skills and the ability to explain technical concepts clearly to engineering partners and other stakeholders; A systems-thinking mindset and a passion for building simple, reliable, and scalable infrastructure platforms.

Nice to have

Experience supporting AI/ML or LLM infrastructure at scale; Experience operating GPU fleets, high-performance compute infrastructure, or large-scale capacity planning; Experience with multi-cloud infrastructure or hybrid cloud environments; Experience building internal platforms or developer tooling that improves engineering velocity and production safety.