AI Platform Engineer — MLOps & Cloud Foundations

Jobtailor; California (MO); Hybrid; USD 140,000 - 190,000; Full time

Job summary

HARMAN is seeking a senior Platform Engineer to develop and maintain an enterprise AI platform in a hybrid Novi, MI environment. You will build cloud-native solutions, implement MLOps practices, and collaborate with security and architecture teams to enforce governance and reliability.

The role requires 6+ years in platform or cloud engineering, strong experience with Azure/AWS/Kubernetes, and a focus on scalable, secure AI workloads. Travel up to 20% and a background check are required.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field
• 6+ years of experience in platform engineering, cloud engineering, software engineering, or related disciplines
• Strong experience developing and operating cloud-native platforms using Microsoft Azure, AWS, or similar enterprise cloud environments
• Hands-on experience with MLOps, LLMOps, CI/CD automation, infrastructure-as-code, containerization, and production deployment practices
• Strong understanding of platform security, identity and access management, observability, monitoring, and security-by-design principles
• Knowledge of data governance, enterprise integration patterns, APIs, and scalable platform architectures supporting AI and data-driven solutions
• Willingness to travel 20% of the time
• Willingness to work hybrid in the HARMAN Novi, MI office 3+ days a week
• Successful completion of a background investigation and drug screen required
• Nice-to-have: experience supporting enterprise AI platforms, agent-based systems, RAG, or generative AI workloads
• Nice-to-have: certifications in Azure, AWS, Kubernetes, DevOps, Security, or related cloud technologies
• Nice-to-have: experience with vector databases, AI orchestration frameworks, model serving platforms, and modern AI development ecosystems
• Nice-to-have: experience working in large, global organizations with distributed engineering and operations teams

Responsibilities

• Develop, deploy, and maintain enterprise AI platform components, services, APIs, and integrations
• Execute platform architecture designs and implement reusable platform capabilities aligned with enterprise standards and reference architectures
• Build and maintain CI/CD pipelines, automation frameworks, and deployment processes supporting AI workloads and platform services
• Perform testing, validation, and operational readiness assessments for platform modules, services, and integrations
• Implement and support MLOps and LLMOps processes, including model deployment, monitoring, versioning, lifecycle management, and operational governance
• Ensure platform solutions meet enterprise requirements for security, scalability, reliability, observability, and performance
• Collaborate with data, security, and architecture teams to implement governance controls, access management, and compliance requirements
• Monitor platform health, troubleshoot production issues, optimize performance, and drive continuous operational improvements
• Contribute to platform documentation, technical standards, reusable assets, and engineering best practices
• Evaluate emerging technologies and recommend enhancements that improve platform capabilities and developer experience
• Collaborate with AI architects, platform engineers, product owners, security teams, data engineers, and application developers to build, operate, and continuously improve HARMAN’s enterprise AI platform ecosystem

Skills

MLOps

LLMOps

CI/CD Automation

Infrastructure as Code

Containerization

APIs

Data Governance

Platform Architecture

Production Deployment

Observability

Education

Bachelor’s degree

Tools

Microsoft Azure

AWS

Kubernetes

DevOps

Vector Databases

AI Orchestration Frameworks

Model Serving Platforms

Job description

HARMAN is seeking a senior Platform Engineer to develop and maintain an enterprise AI platform in a hybrid Novi, MI environment. You will build cloud-native solutions, implement MLOps practices, and collaborate with security and architecture teams to enforce governance and reliability.

The role requires 6+ years in platform or cloud engineering, strong experience with Azure/AWS/Kubernetes, and a focus on scalable, secure AI workloads. Travel up to 20% and a background check are required.