Designs and builds scalable multi-cloud infrastructure (Azure, GCP) powering AI platform, including Kubernetes orchestration, observability, and distributed systems for reliability at massive scale. Requires 10+ years in infrastructure engineering with IaC expertise.
236k – 290k/yr
On-site10+ YOEDevOps / SRE
About the role
What You’ll Do
Design and build scalable, fault-tolerant infrastructure systems that power Harvey's AI platform across multiple cloud regions
Own and evolve our multi-cloud infrastructure (Azure, GCP), including Kubernetes orchestration, networking, and container management
Lead technical initiatives around observability, incident response, and operational excellence — building systems that enable rapid detection and resolution of issues
Architect and optimize our distributed systems for reliability, including load balancing, quota management, and failover mechanisms
Partner with Product Engineering and Security teams to ensure our infrastructure is an accelerant, not a constraint
Drive infrastructure-as-code practices using tools like Terraform and Pulumi to enable reproducible, auditable deployments
Mentor engineers and raise the technical bar across the organization through code reviews, design reviews, and technical leadership
Representative Projects
Design and implement a next-generation model proxy architecture that routes millions of daily inference requests while maintaining model API compatibility and enabling seamless model integration
Build distributed rate limiting and quota management systems using Redis-backed algorithms to handle bursty traffic patterns without degrading user experience
Architect multi-region deployment strategies that meet strict data residency requirements for global enterprise customers
Develop comprehensive observability infrastructure with granular SLA monitoring, burn rate alerts, and detailed token attribution for cost tracking
Lead the evolution of our CI/CD pipelines to improve developer velocity while maintaining production stability
What You Have
10+ years of experience in Infrastructure Engineering or Platform Engineering in a production environment
Long track record building and scaling complex, large-scale distributed systems
Deep proficiency with cloud infrastructure platforms (Azure preferred; GCP or AWS experience transfers well)
Strong fluency in Infrastructure as Code (IaC) tools — Terraform, Pulumi, or CloudFormation
Solid understanding of Kubernetes, container orchestration, networking, and cloud security at scale
Experience with observability tools (Datadog, Sentry) and incident response practices (PagerDuty, Incident.io)
Strong programming skills in Python, Go, or similar languages
Excellent problem-solving skills, a "spidey sense" of where things could go wrong, and a commitment to operational excellence
Nice to Have
Experience building infrastructure for AI/ML workloads or high-throughput inference systems
Background with distributed rate limiting, load balancing, or quota management systems
Experience operating multi-tenant platforms with strict security and compliance requirements
Track record of leading complex cross-functional projects and delivering measurable impact
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