Job Url: https://www.indeed.com/viewjob?jk=6735e802e44bf9b9&tk=1j320815oi8ql8bc&from=serp&vjs=3

Job Description: Job details
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Pay

$167,249 - $216,000 a year
Job type

Full-time
 
Full job description
Virta Health is pioneering a new standard of care for people to reclaim their lives. We are in the midst of a public health crisis: obesity rates are at an all-time high and over half of US adults have type 2 diabetes or prediabetes, and despite billions spent on new treatments, outcomes are largely worse. Virta reverses these diseases and delivers life-changing results by pairing individualized nutrition with ongoing care from a clinical support team. 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 take back their lives.

As a Senior Software Engineer for AI & Automation on our AI Enablement Team, you will rapidly build impactful workflow and AI-driven product solutions from discovery to production readiness. You'll actively use cutting-edge AI tools including agents and LLMs to automate internal processes and enhance productivity. Working closely with Subject Matter Experts (SMEs) and stakeholders across diverse teams you'll autonomously craft solutions that reliably address real-world business challenges. This role is perfect for engineers motivated by tangible impact, autonomy, and continuous learning.

What You'll Do
As an AI & Automation Engineer, you’ll embed with cross-functional teams to understand their most onerous manual processes, then prototype, deploy, and own automated solutions. In doing so you will provide invaluable feedback to our platform teams on gaps in our existing software delivery lifecycle.

Collaborate with SMEs and cross-functional teams during initial discovery to understand business challenges and define success metrics.

Rapidly prototype Workflow and AI-enabled automations.

Independently drive solutions from initial prototype through to robust, production-grade deployment within a 4–6 week cycle.

Continuously provide feedback to platform teams on gaps in development workflow, infrastructure, observability, library abstractions, and ci/cd.

Continuously automate your own processes using AI, enhancing efficiency and accelerating development timelines.

Maintain active engagement with stakeholders to ensure adoption and refine solutions based on feedback.

Stay updated on advancements in AI models and tools, proactively applying relevant developments to enhance your solutions.