Why This Role Stands Out
You'll lead the architectural strategy and security framework for enterprise AI/ML platforms in a remote, growth-oriented role with significant impact. This is an excellent opportunity for a seasoned DevSecOps professional with a passion for AI and MLOps to shape cutting-edge platforms and drive innovation. Apply today to join a forward-thinking team!
Quick Overview
Job Description
DevSecOps Lead Engineer with AI Platform
Remote for now
Job Description :
Position Summary
- As a Lead Engineer specializing in DevSecOps on the AI Platform Team within Optum AI, you will drive the architectural strategy, automated infrastructure delivery, and security framework for our enterprise AI/ML platforms across multi-cloud environments, with a primary focus on Google Cloud Platform In this senior hands-on technical lead role,
- you will integrate robust DevSecOps and MLOps practices into our core AI platform, ensuring continuous delivery, robust vulnerability management, AI security guardrails, and strict compliance.
Work Location Policy:
This position is open to 100% remote candidates residing anywhere in the U.S. For any hires residing in the Minneapolis, MN or Washington, D.C. areas, you will follow a hybrid model requiring in-office work a minimum of four days per week.
Primary Responsibilities
- Lead the architectural design DevSecOps framework and infrastructure as code automation for multi-cloud AI/ML platforms with dedicated focus on Google Cloud Platform
- Represent the AI platform organization in enterprise security architecture reviews threat modeling vulnerability management assessments and compliance audits
- Architect build and maintain secure automated CI CD and MLOps pipelines for AI model training deployment, tracking, monitoring and lifecycle management
- Partner with cross functional software engineering data science product management and cybersecurity teams to enforce security best practices across the AI lifecycle
- Provide technical leadership architectural guidance code reviews and mentorship to DevOps MLOps, and AI/ML engineers across the team
Required Qualifications
- Bachelors degree or 8+ additional years of software development DevSecOps or infrastructure engineering experience in lieu of a degree
- 8 years of experience in Software Engineering Infrastructure Engineering or DevOps with at least
- 4+ years dedicated to DevSecOps and Cloud Security 4 years of hands on experience designing building and securing enterprise cloud infrastructure across cloud providers, with dedicated expertise in Google Cloud Platform
- 4 years of experience in a technical lead or architectural leadership role
- 3 years of experience implementing CI CD pipelines policy as code and automated security scanning toolsCISSP CISM or DevSecOps professional security certification
- Experience with healthcare data standards and security/compliance protocols
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