Why This Job is Featured on The SaaS Jobs
Core infrastructure roles are a cornerstone of modern SaaS, and this one sits close to the “platform as a product” layer that determines reliability and trust for enterprise buyers. The listing signals a high-usage, globally distributed AI SaaS with meaningful operational constraints, where multi-cloud, Kubernetes, and region-aware deployment patterns are not theoretical but day-to-day realities. That combination places the work at the intersection of classic SaaS scalability and newer AI workload characteristics like bursty inference traffic and cost attribution.
For a SaaS career, the long-term value is in building repeatable systems for multi-tenant scale: infrastructure as code, observability tied to SLAs, incident response maturity, and mechanisms like quota management that directly shape customer experience. Experience designing for data residency and production resilience translates well across enterprise SaaS, especially for companies moving from single-region setups to global footprints and stricter security expectations.
This role fits engineers who prefer owning foundational systems over feature delivery, and who enjoy balancing new build with hardening what already runs in production. It also suits someone comfortable partnering across product engineering and security, and who is motivated by measurable outcomes such as reliability, latency, and operational efficiency rather than purely roadmap throughput.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Why Harvey
At Harvey, we’re transforming how legal and professional services operate — not incrementally, but end-to-end. 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. With 1000+ customers in 58+ countries, 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 is sharp, motivated, and deeply committed to the mission. We move fast, operate with intensity, and take real ownership of the problems we tackle — from early thinking to long-term outcomes. We stay close to our customers — from leadership to engineers — and work together to solve real problems with urgency and care. If you thrive in ambiguity, push for excellence, and want to help shape the future of work alongside others who raise the bar, we invite you to build with us.
At Harvey, the future of professional services is being written today — and we’re just getting started.
Role Overview
As a Software Engineer on the Core Infrastructure team at Harvey, you'll play a critical role in designing and building new infrastructure systems while equally scaling and strengthening our existing infrastructure. Our infrastructure is the foundation that powers every user interaction with Harvey — processing billions of prompt tokens and millions of daily requests across our global legal AI platform.
You'll work in an environment balanced between innovation — building new systems — and operational excellence, ensuring that Harvey remains resilient and efficient as it scales products, regions, customers, and usage. Your contributions will directly impact the reliability, scalability, and security of our platform as we serve the world's leading law firms and professional service providers.
This role is based in San Francisco, CA. We use an in-person work model and offer relocation assistance to new employees.
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 junior / intern 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
4+ 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
Compensation Range
$201,000 - $264,000 USD
Please find our CA applicant privacy notice here.
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Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
