Engineering Manager/TLM, Platform

Harper•San Francisco, CA

8d•$225,000 - $275,000•Onsite

About The Position

Harper is building the inverse of the traditional insurance distribution system, aiming for AI-led operations rather than human-led ones. The company is experiencing rapid growth, adding approximately 1,000 customers per month and growing 100x since last year. This role is crucial for building the team and systems that the rest of engineering depends on, enabling faster compounding growth. The platform engineering at Harper is designed to be the engine that allows product teams to ship quickly, ensuring that observability catches issues before customers do, infrastructure prevents problems like connection exhaustion, and developer velocity is enhanced through the creation of essential tools. The company operates over 200 services across Railway and AWS, orchestrating numerous parallel agentic workloads and making thousands of AI-driven decisions daily, all of which require traceability, evaluation, and cost optimization.

Requirements

At least 2 years as a line manager directly managing teams of six to ten people—or clear readiness to grow into that role
You've been a line manager for at least two years, directly managing teams of six to ten people—or you're on a clear path there and want to grow into it
Hands-on experience with AWS or GCP and strong database troubleshooting skills
Seen real scale—on the order of at least a million requests per minute
Can troubleshoot across databases, networking, compute, Docker, Kubernetes, and other aspects of infrastructure
Care as much about developer productivity and AI tooling as you do about raw infrastructure
Know on-call practices, SLAs, SLOs, and SRE practices generally
Want to stay hands-on and grow into a fuller managerial role over time
Move fast, with the same appetite as the rest of Harper

Nice To Haves

Your own network to draw on for hiring—otherwise, comfort working closely with recruiters
Experience building developer productivity tooling and AI harnesses for other engineering teams
Experience building a team from a very small base
Prior startup experience—especially at a company scaling through hypergrowth

Responsibilities

Own infrastructure — cloud, third-party vendors, and everything surrounding it
Build developer productivity — the AI tooling and harnesses that make every other engineering team genuinely AI-first
Own SRE and production support — bring production discipline as we head into a high-growth, high-scale phase
Build out the team — grow from 2 people to five to six over the next three months
Stay hands-on — with a team this small, work directly alongside your engineers and do the work yourself, not just direct it
Grow each function over time — infrastructure, developer productivity, and SRE/production support can each become a larger team of its own