Senior Site Reliability Engineer

Job Overview

Virta Health is on a mission to transform diabetes care and reverse the type 2 diabetes epidemic. Current treatment approaches aren’t working—over half of US adults have either type 2 diabetes or prediabetes. Virta is changing this by helping people reverse type 2 diabetes through innovations in technology, personalized nutrition, and virtual care delivery reinvented from the ground up. We have raised over $350 million from top-tier investors, and partner with the largest health plans, employers, and government organizations to help their employees and members restore their health and live diabetes-free. Join us on our mission to reverse diabetes in 100M.

Key Responsibilities

As an SRE on the Infrastructure team at Virta, you will be building the foundation that will help our company move as fast as possible while meeting security and compliance requirements.

• Implement an AI-driven observability and metrics platform that automatically detects anomalies and highlights SLO risks, enabling product teams to make data-driven decisions.


• Enhance system observability, reliability, and efficiency using off-the-shelf technology combined with internal tools developed in Python and Go to increase transparency and visibility into our systems as well as centralizing data.


• Build out more products for our Product Development teams like observability (SLOs, alerting, dashboards) modules to allow them to spin up an MVP out of the box.


• Improve incident readiness with better tooling and the right hygiene practices such as game days.


• Engage with feature development teams in toil reduction exercises, capacity planning, load testing, SLO process, and other best practices — partnering with product teams to replace manual capacity planning with predictive/AI-driven scaling models and to codify self-healing runbooks that minimize toil


• Improve the velocity and quality of our developer platform and tooling


• General AI fluency desired: comfortable with concepts like prompt engineering, operational chatbots, and AI-assisted workflows to accelerate incident response and reliability improvements

Required Qualifications

• Ship automation and tooling that reduces toil, with high-quality, well-structured code.


• Design and codify self-healing workflows and guardrails to minimize toil and improve reliability.


• Steward SLO dashboards enhanced with AI/ML-assisted insights, leveraging AIOps-style observability to surface anomalies, predict error-budget burn, and improve signal quality across golden signals


• Integrate load-testing into reliability engineering efforts, ensuring outcomes directly inform SLOs, scaling strategies, and capacity planning.


• Partner with product teams to replace manual capacity planning with predictive/AI-driven scaling models and implement burn-rate based alerting.


• Coach and mentor engineers; champion best practices and pragmatic reliability trade-offs.