[Hiring] AI Platform Engineer @NEORIS

Role Description

We are looking for a Principal AI Platform Engineer to:

• Define and evolve the target architecture and roadmap for enterprise-scale Data and AI platforms, covering experimentation, training, feature management, model registry, CI/CD, serving, and observability.
• Design and build multi-tenant, multi-region, highly available AI platforms with clear governance and guardrails.
• Partner with product management to define platform vision, backlogs, OKRs, and golden paths that enable self-service from ideation to production.
• Lead capacity planning and cost optimization strategies for GPU and CPU workloads, driving performance and scalability for distributed training and inference.
• Integrate AI platforms with enterprise data ecosystems to enable governed, reproducible, and scalable ML pipelines.
• Act as a technical leader, translating complex platform concepts into clear value propositions for senior stakeholders across R&D, Commercial, and Operations.

Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related quantitative field.
• Proven experience as a platform or infrastructure engineer supporting ML/AI at scale.
• Hands-on experience with Domino Data Lab.
• Strong experience with AWS (or equivalent cloud providers), including compute, storage, networking, IAM, and cost management.
• Production experience administering EKS clusters, including GPU workloads, operators, storage classes, and service mesh.
• Strong Python development experience, especially for platform automation and tooling.
• Solid background in Infrastructure as Code (Terraform, CloudFormation or similar).
• Experience with MLOps practices: model pipelines, lifecycle management, CI/CD, and monitoring.
• Experience with LLM serving, RAG architectures, vector databases, prompt safety, and token-aware scaling.
• Experience designing and operating agentic systems, including multi-agent orchestration, tool/action frameworks, safety guardrails, and evaluation of reliability and cost.

Requirements

• Experience with Apache Spark and large-scale data processing platforms.
• Familiarity with GxP or regulated environments.
• Experience working closely with cybersecurity and data privacy teams.
• Exposure to AIOps practices and advanced observability tooling.
• Cloud or Kubernetes-related certifications.

Benefits

• Permanent contract with a competitive salary.
• Flexible working model with remote work options.
• Personalized career path and continuous learning (certifications, English training, etc.).
• Participation in stable, long-term projects with high technical complexity.
• Flexible working hours and strong work-life balance focus.
• Social benefits package tailored to your needs.