R&D AI DevOps Leader

3MMaplewood, MN
Onsite

About The Position

Collaborate with Innovative 3Mers Around the World. This position provides an opportunity to transition from other private, public, government or military experience to a 3M career. As an R&D AI‑DevOps Leader, you will play a critical role in enabling how high‑sensitivity AI research and algorithms move from development to protected, enterprise‑ready deployment. You will be responsible for standing up and operating a secure, on‑prem GitHub Enterprise environment and architecting end‑to‑end DevOps and CI/CD pipelines tailored for highly sensitive, trade‑secret AI systems. This role is designed for a senior technical leader who thrives at the intersection of AI engineering, secure platform architecture, and enterprise DevOps transformation. You will partner closely with AI researchers, software engineers, infrastructure and security teams, and senior leaders to ensure advanced algorithms and systems can be developed rapidly—while meeting the highest standards for security, traceability, and IP protection. You will enable teams developing new‑to‑world AI, optimization, and experimental systems by providing the platform architecture, security controls, and delivery discipline required to operate across Tier 0 to Tier 2 security layers in highly regulated and IP‑sensitive environments.

Requirements

  • Bachelor's Degree in Computer Science, Information Science, Systems Engineering, or a related technical discipline (completed and verified prior to start) from an accredited institution.
  • 5+ years of experience delivering complex software, cloud, or platform initiatives spanning DevOps, infrastructure, data, or AI‑enabled systems.

Nice To Haves

  • Proven experience architecting and operating secure DevOps and CI/CD platforms in enterprise or highly regulated environments. (Healthcare, government or defense sectors)
  • Strong working fluency in AI, machine learning, and algorithm‑driven systems, with the ability to partner credibly with research and engineering teams.
  • Demonstrated ability to influence senior technical and business leaders and align stakeholders across R&D, engineering, security, and platform teams.
  • Experience designing or operating secure code environments for trade secrets, regulated IP, or highly sensitive algorithms.
  • Familiarity with AI governance, model lifecycle management, and secure deployment patterns for ML and LLM‑based systems.
  • Experience authoring or operationalizing secure reference architectures and repeatable DevOps patterns at scale.
  • Background working with on‑prem, hybrid, or multi‑cloud enterprise environments, including identity, access, and network security considerations.
  • Experience working in Agile / iterative delivery environments, balancing platform reliability with rapid innovation.
  • Excellent executive communication skills—able to make complex security and architecture decisions transparent and decision‑ready.

Responsibilities

  • Design, stand up, and operate GitHub Enterprise (on‑prem) as the core source‑control and collaboration platform for sensitive AI and algorithm development.
  • Architect and implement secure, end‑to‑end CI/CD pipelines supporting AI, data‑intensive, and experimental codebases from research through deployment.
  • Define and enforce tiered security architectures (Tier 0–Tier 2), including access controls, isolation boundaries, promotion paths, and release readiness criteria for trade‑secret code.
  • Establish secure DevOps standards and practices that balance research velocity with enterprise‑grade controls, auditability, and compliance.
  • Partner with AI researchers, software engineers, infrastructure, and security teams to operationalize machine learning, LLM, and optimization systems in protected environments.
  • Implement governance, automation, and monitoring to ensure reproducibility, traceability, and risk management across the AI development lifecycle.
  • Serve as a technical and strategic bridge—translating security, DevOps architecture, and platform tradeoffs into clear guidance for executive and research leadership.

Benefits

  • Medical, Dental & Vision
  • Health Savings Accounts
  • Health Care & Dependent Care Flexible Spending Accounts
  • Disability Benefits
  • Life Insurance
  • Voluntary Benefits
  • Paid Absences
  • Retirement Benefits
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