Principal Cloud Engineer – AI/ML

Anticipated End Date: 2026-09-21 Position Title: Principal Cloud Engineer – AI/ML Job Description: Principal Cloud Engineer – AI/ML Location: This role requires associates to be in-office 1 - 2 days per week, fostering collaboration and connectivity, while providing flexibility to support productivity and work-life balance. This approach combines structured office engagement with the autonomy of virtual work, promoting a dynamic and adaptable workplace.

Alternate locations may be considered if candidates reside within a commuting distance from an office. Please note that per our policy on hybrid/virtual work, candidates not within a reasonable commuting distance from the posting location(s) will not be considered for employment, unless an accommodation is granted as required by law. PLEASE NOTE: This position is not eligible for current or future visa sponsorship.

At Elevance Health, Cloud Engineering builds and operates secure, scalable platforms that help application teams provision environments, deploy workloads, manage cloud cost, and transform applications. The Principal Cloud Engineer - AI/ML is a hands-on principal engineer within the Cloud organization. This role designs, codes, integrates, and operates AI-enabled capabilities across account vending and landing zones, Containers as a Service (CaaS), FinOps, developer onboarding, and application migration and transformation.

The Principal Cloud Engineer – AI/ML creates production agents, reusable agent skills, and Model Context Protocol (MCP) servers and integrations that make cloud services easier to consume and operate . The role partners with Enterprise AI, Information Security, Responsible AI, Enterprise Architecture, and application teams to apply enterprise standards and approved AI services within cloud products.

A substantial portion of the role is hands-on build and production ownership. Success is measured through working software, customer adoption, faster onboarding and provisioning, improved developer experience, lower cloud cost, more reliable operations, and accelerated application transformation. How you will make an Impact: Deploy AI-enabled capabilities for core Cloud Engineering products, with regular hands-on work in application code, infrastructure as code, APIs, CI/CD pipelines, and production environments.

Develop production agents and reusable skills for cloud customer journeys, including account, subscription, and project requests; landing-zone configuration; access and policy validation; deployment guidance; incident triage; CaaS troubleshooting; cost optimization; and migration readiness. Build and maintain MCP servers, adapters, and supporting services that securely expose cloud platform APIs, automation, inventory, telemetry, cost data, and operational knowledge to approved agents and assistants.

Advance account vending and developer onboarding by automating intake, prerequisite checks, guardrail validation, documentation, environment setup, access workflows, and handoff to platform services, reducing time to first productive deployment. ​ Enhance CaaS offerings through self-service and AI-assisted capabilities for workload onboarding, deployment, policy compliance, observability, troubleshooting, and guided remediation across Kubernetes-based environments.

Create FinOps tooling and agents for allocation and tagging quality, anomaly detection, rightsizing, forecasting, commitment utilization , waste reduction, and actionable optimization recommendations; measure realized savings and cost avoidance. ​ Build application transformation accelerators for discovery, dependency analysis, cloud readiness, containerization, migration planning, modernization recommendations, and generation of repeatable implementation artifacts.

Partner with Enterprise AI, Information Security, Responsible AI, and Enterprise Architecture to consume standards, integrate approved models and tooling, complete security and risk reviews, and implement iden