Platform Engineer

Harper•San Francisco, CA

4h•$140,000 - $280,000•Onsite

About The Position

The Problem: 36 million businesses in America need insurance—it's not optional. 77% are underinsured. 40% have no coverage at all. The distribution system failed them: too slow, too opaque, too confusing. Over 90% of commercial insurance is still human-led. We're building the inverse: 90%+ AI-led, pushing toward the higher 90s. Not by patching legacy workflows—by building AI that makes humans more effective, improves the customer experience, and eliminates friction at every step. We're adding ~1,000 customers per month. We've grown 100x since last year. We're looking to do even more this year—and that's why we're hiring. You build the systems the rest of engineering depends on. When they compound, everyone gets faster. The Thesis: Harper runs 200+ services across Railway and AWS. We orchestrate N parallel agentic workloads. Our AI systems make thousands of decisions a day, and every decision needs to be traceable, evaluated, and cheaper to run tomorrow than it is today. The infrastructure underneath all of that is the difference between a company that scales and one that stalls. Great platform engineering here isn't invisible—it's the reason product ships fast. When observability catches a silent failure before a customer does. When a pooling layer makes connection exhaustion a non-issue. When developer velocity doubles because someone built the tool nobody knew they needed. That leverage compounds across every other engineer on the team. The Role: You're an infrastructure-focused engineer with depth across databases, AWS, networking, observability, SRE, CI/CD, and AI tooling. You build the systems and tooling the rest of engineering depends on—optimized for performance, reliability, and developer velocity. You work directly with founders and alongside the product engineers who ship features on top of what you build. You see where things break at scale, design the fix, and ship it before it becomes a fire. When something goes wrong at 2 AM, you're the one who gets paged—and you'd rather build the system that prevents the page than accept it as inevitable. We are hiring platform engineers across all levels, which we determine during the interview process.

Requirements

Software engineering experience with a platform, infrastructure, or SRE focus (level determined during interviews)
Proficiency in Python, TypeScript, Go, or similar
Production experience with cloud infrastructure (AWS), databases (Postgres), and observability tooling
Track record of building systems and tooling that other engineers depend on
Based in San Francisco or willing to relocate

Nice To Haves

Experience orchestrating AI/ML workloads at scale (agent frameworks, LLM inference infrastructure)
Voice AI or real-time systems experience
Deep AWS experience (ECS, Lambda, RDS, VPC design)
Prior startup experience—especially at companies that scaled through hypergrowth

Responsibilities

Own core infrastructure — Databases, AWS services, networking, CI/CD; the systems every engineer depends on
Build for scale — Thousands of concurrent AI operations, sub-second response times, cost-effective under load
Design observability that works — System-level errors AND business-level silent-failure detection; we find out something is broken from an alert, not from a person hours later
Orchestrate agentic workloads — N parallel agent instances doing non-deterministic work, running reliably and cost-effectively as N grows
Multiply developer velocity — The tooling and abstractions that let product engineers ship in days instead of weeks
Own reliability end-to-end — SLOs, on-call, incident response, and the post-mortems that make it rarer next time
Build the eval infrastructure — Systems that measure whether AI outputs are getting better, not just running