AI/ML DevOps Engineer, Senior Advisor II

Remote Full-time
** U.S. work authorization required. No sponsorship or third-party engagements available.**

Job Title: AI/ML DevOps Engineer, Senior Advisor II

Duration: 2 year contract, potential perm after 1 year

Location: 100% Remote

About the Team

The AI Development team at Client is dedicated to accelerating the adoption of AI across the enterprise. We stay at the forefront of AI advancements to upskill teams, embed AI into relevant job functions, expand access to AI tools, and deploy intelligent agents that boost quality and productivity. We also enhance Client’s customer-facing products with AI-driven capabilities to deliver smarter, more efficient experiences.

What does a Senior Advisor do?

As a staff-level individual contributor, the Senior Advisor plays a critical role in accelerating Client’s AI transformation. This role combines deep expertise in DevOps and infrastructure-as-code with a forward-looking approach to integrating AI across the software development lifecycle (SDLC).

What you will do:
• Act as a trusted internal subject matter expert, guiding teams on secure, scalable cloud architecture that leverages AI technologies.
• Enhances the Software Development Lifecycle by embedding AI into CI/CD pipelines, testing, monitoring, and deployment processes.
• Build and optimize cloud environments with a focus on automation, security, and AI readiness.
• Partner across teams to identify opportunities where AI can improve velocity, quality, and operational efficiency.
• Stay ahead of emerging trends to ensure Client’s platforms and practices remain modern, resilient, and AI-enabled.

What you will need:
• Bachelor’s or master’s degree in computer science, Engineering, or a related technical field - or equivalent practical experience.
• 20+ years of industry experience in software engineering, DevOps, and infrastructure architecture.
• Deep expertise in DevOps and MLOps practices, with a strong track record of automating and optimizing the software development lifecycle.
• Hands-on experience with Infrastructure as Code (IaC) using Terraform, including multi-cloud provisioning and policy enforcement.
• Proven ability to design and manage secure, scalable environments across GCP, Azure, and AWS.
• Strong understanding of AI/ML technologies and how to integrate them into cloud-native architectures and CI/CD pipelines.
• Demonstrated ability to serve as a technical advisor and internal consultant, accelerating projects through deep domain knowledge and cross-functional collaboration.
• Familiarity with containerization (e.g., Docker, Kubernetes), observability tools, and modern SDLC tooling.
• Excellent communication and mentoring skills, with the ability to influence technical direction across teams.

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