DevOps AI Platform Engineer Lehi, Utah (Hybrid, onsite 3 days each week) Direct Hire Pay Rate: $220-280K
Our client needs to hire a DevOps AI Platform Engineer to operationalize AI across the engineering and product delivery pipeline (engineering, product, UX, and the broader customer value stream). This person will identify bottlenecks in how work moves from idea to shipped product, stay obsessively current on AI best practices, translate that knowledge into actionable standards and systems, and drive adoption at scale through enablement, tooling, and repeatable platform patterns. The intent is to bring in someone who can lead meaningful AI-driven transformation—starting with developer systems first, with potential to expand broader organizational impact over time.
Responsibilities:
Lead the implementation and operationalization of AI capabilities within the engineering organization, integrating AI tools into daily development workflows.
Design and maintain AI-enabled engineering platforms using services within Amazon Web Services, ensuring scalability, reliability, and security.
Build and improve developer workflows and automation across the software development lifecycle (SDLC), including CI/CD pipelines and developer tooling.
Develop architectural patterns, guardrails, and validation frameworks to ensure responsible and effective use of AI across engineering teams.
Evaluate and implement AI-powered tools and frameworks to improve developer productivity and engineering efficiency.
Partner with Engineering, Product, and UX teams to drive adoption of AI-assisted development workflows and improve cross-team processes.
Establish standards, best practices, and governance models for AI usage within engineering platforms.
Continuously research emerging AI technologies and translate them into practical improvements for internal engineering systems.
Required Skills:
8+ years of experience
Demonstrated ability to operationalize AI in real engineering orgs
Strong AWS fundamentals and understanding of integrating services into platform systems
SDLC / CI/CD depth and familiarity with developer workflow mechanics
High learning velocity and obsession with staying current in AI
Architectural thinking — ability to design patterns, guardrails, and validation layers
Proven ability to influence and drive workflow change across Engineering, Product, and UX
Bonus Skills:
AI-specific security or validation layer experience
Background evolving from DevOps into AI Platform or AI SecOps
Experience building shared AI capabilities (e.g., internal plugin repositories or shared tooling frameworks)
Strong evaluation instincts around emerging AI practices
Candidates who are ahead of current mid-market SaaS AI maturity