Principal AI Platform Engineer

What’s the role?

We are looking for a strong AI Platform Engineer to build and operate the AI Hub that powers AI delivery. Working closely with AI Architects, Automation Engineers, Data Engineers, and Security teams, this role is responsible for the shared runtime, CI/CD pipelines, model registry, observability platform, and developer frameworks that enable teams to rapidly build, deploy, and govern AI solutions. The Platform Engineer ensures AI capabilities are secure, scalable, compliant, cost-efficient, and reusable, allowing the CoE to operate as an enterprise platform team rather than a collection of one-off projects.

What You’ll Do

• Design, build, and operate the enterprise AI Hub, providing shared services, deployment frameworks, and developer tooling for AI applications and intelligent agents.
• Develop and maintain CI/CD pipelines, infrastructure-as-code, automated testing, and release processes for AI and machine learning workloads.
• Implement and manage model registries, prompt repositories, vector database integrations, orchestration frameworks, and agent runtime environments.
• Build and operate observability solutions that provide monitoring, logging, tracing, performance metrics, and cost visibility across AI platforms.
• Establish and enforce platform standards for security, identity management, governance, compliance, auditability, and responsible AI practices.
• Partner with AI Architects to translate platform designs into scalable production environments and reusable platform services.
• Enable Automation Engineers and product teams by creating self-service capabilities, templates, SDKs, reference architectures, and reusable components.
• Optimize platform reliability, performance, scalability, and operational efficiency while maintaining service-level objectives.
• Manage cloud-native AI infrastructure across cloud and hybrid environments, including containerized and serverless workloads.
• Drive platform automation, reducing manual operational effort through infrastructure-as-code, policy-as-code, and automated governance controls.
• Evaluate and integrate emerging AI infrastructure technologies, frameworks, and tools to continuously improve the AI ecosystem.
• Monitor platform costs, resource utilization, and licensing consumption, identifying opportunities to improve efficiency and governance.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent practical experience.
• 5+ years of experience in platform engineering, cloud engineering, DevOps, Site Reliability Engineering (SRE), or infrastructure engineering roles.
• Hands-on experience designing and operating cloud platforms.
• Strong expertise with infrastructure-as-code technologies.
• Experience building and supporting CI/CD pipelines using GitHub Actions, Azure DevOps, GitLab, Jenkins, or similar platforms.
• Deep understanding of containerization and orchestration technologies, including Docker and Kubernetes.
• Experience implementing monitoring, logging, tracing, and observability solutions using tools such as Datadog, Grafana, Prometheus, OpenTelemetry, or Splunk.
• Strong understanding of identity, access management, secrets management, and enterprise security controls.
• Experience supporting scalable production systems with high availability and operational resilience requirements.
• Strong scripting and automation skills using Python, PowerShell, Bash, or similar technologies.
• Experience supporting AI, machine learning, or GenAI platforms in production environments.
• Familiarity with model lifecycle management, MLOps, LLMOps, model registries, and AI governance frameworks.
• Experience with AI technologies such as Azure AI Services, Azure OpenAI, AWS Bedrock, Databricks, LangChain, Semantic Kernel, or vector databases.
• Knowledge of Responsible AI principles, model monitoring, prompt management, and AI compliance requirements.
• Experience developing internal developer platforms and self-service engineering capabilities.
• Relevant cloud certifications in Azure, AWS, Kubernetes, Terraform, or similar technologies.

What we offer

• Work on globally deployed automotive navigation and mapping products.
• Collaboration with an experienced, international engineering organization.
• International team with colleagues across Europe, the US, Asia, and other locations.
• Flexible working hours and a flexible approach to office versus remote work.
• Yearly variable bonus.

Candidates must successfully complete a pre-employment screening process. This may involve employment, education, and criminal verification, where applicable. This offer and any related claims are subject to successful completion of the screening process.