Senior Platform Engineer

Doctronic•San Francisco, CA

1d•$180,000 - $240,000•Onsite

About The Position

Doctronic gives people free, private access to AI health guidance and affordable visits with human physicians. Millions of consultations already depend on our production systems. We are hiring a Senior Platform Engineer to improve the systems used to build, deploy, observe, and operate Doctronic. This role owns engineering enablement, including the environment in which engineers and coding agents understand the codebase, make changes, validate them, and ship.

Requirements

Experience building and operating production systems on AWS.
Strong knowledge of containers, infrastructure as code, CI/CD, networking, and observability.
Experience with container orchestration and automated delivery.
Experience improving developer environments, CI performance, service templates, or internal engineering tools.
The ability to write software and automation instead of relying on manual procedures.
Daily experience with coding agents and evidence that you have built tools, context, or workflows that make them more reliable.
Experience measuring or improving engineering throughput, CI time, test quality, or self-service adoption.
Experience diagnosing incidents and making follow-up improvements.
Good judgment about reliability, security, cost, and delivery speed.
Clear written and verbal communication across engineering teams.

Nice To Haves

Experience with AI infrastructure, regulated systems, disaster recovery, or high-traffic applications is useful but not required.

Responsibilities

Improve the reliability and operation of production services on AWS ECS.
Build shared infrastructure, service templates, and delivery workflows that reduce the time from code to production.
Improve local development, CI, test, and deployment workflows so engineers can work without platform support for routine tasks.
Build agent-ready repositories, documentation, and interfaces so coding agents can complete useful tasks with less supervision.
Automate recurring work such as service setup, dependency changes, release checks, and incident triage.
Create guardrails and feedback loops that make agent-produced changes fast to validate and safe to ship.
Give engineers useful logs, metrics, alerts, and service health information.
Define practical standards for incident response, recovery, capacity, and service reliability.
Build security, privacy, and compliance controls into infrastructure and delivery workflows.
Track infrastructure cost and improve efficiency as traffic, data, and AI workloads grow.
Work with product, AI, data, and security engineers to solve production problems.