Principal ML & AI Engineer

What's the role?:

The Responsible AI Engineering team is part of the AI & Analytics Infrastructure team, which is building the agentic AI infrastructure and the governance around it. As a member of this team, you will become a subject matter expert in Agentic AI while working across security, OSS compliance, and AI governance domains. You will work with a global team to build tooling, develop technical guardrails, improve compliance processes, and establish best practices for AI-enabled products and services.

Every team in the company wants to adopt AI, and every team operating its own pipelines, serving stack, and monitoring multiplies reliability, security, and cost risk. This role exists to solve that. You will own the MLOps foundation behind the shared AI platform: repeatable delivery pipelines, infrastructure automation, model and prompt lifecycle management, production serving, observability, evaluation, and cost-efficient operations. Instead of each team inventing its own path to production, they build and operate on the paved road you create. This is a hands-on principal engineering role. You will set technical direction, write production code and infrastructure-as-code, establish operational standards, and embed with consuming teams to move AI workloads from prototype to dependable production services. You will work closely with the platform architect and security, identity, data, and application teams in a security-sensitive enterprise environment. Who are you?: * Extensive experience building and operating production MLOps or AI platform capabilities in an enterprise environment. * Strong software engineering skills, especially Python, with a track record of owning systems from design through production operations. * Deep experience with CI/CD, GitOps, infrastructure-as-code, containerized workloads, and automated environment promotion. * Strong AWS-native infrastructure experience, including Bedrock, EC2, IAM, load balancing, netw