NEORIS

AI

PrincipalAIPlatformEngineer

Madrid, Spain CONTRACT Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Principal AI Platform Engineer at NEORIS. Skills: AI Platform Engineering, MLOps, Cloud Infrastructure, Python. Define target architecture. Evolve platform roadmap”

What You'll Achieve.

Deliver real impact; Sustainable growth; High-value outcomes

Industry & Context.

AI
Problems you'll solve

Problem-solving

What They're Looking For.

Must Have

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, 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, 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

Nice to Have

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

What You'll Do.

Define target architecture

Evolve platform roadmap

Design multi-tenant platforms

Build highly available platforms

Partner with product management

Define platform vision

Lead capacity planning

Drive performance and scalability

Integrate AI platforms

Enable governed ML pipelines

Translate platform concepts

Deliver value propositions

How You'll Work.

Team & Collaboration

Partner with product management; Work with senior stakeholders across R&D, Commercial, and Operations; Work closely with cybersecurity and data privacy teams

Communication Scope

Translating complex platform concepts into clear value propositions

Process & Methodology

Define platform roadmaps, Define platform vision, Define backlogs, Define OKRs

Full Job Description

We are the accelerator that drives growth in Ibero‑America, combining EPAM’s global engineering excellence with NEORIS’ regional expertise and cultural proximity. We help organizations scale, modernize, and advance their digital transformation through Cloud, Data & Analytics, Artificial Intelligence, Cybersecurity, Intelligent Automation, Strategic Consulting, and Software Engineering solutions. Backed by more than 60,000 professionals across 55+ countries and a strong Nearshore model, we connect global capabilities with local trust to deliver real impact, sustainable growth, and high‑value outcomes for our clients. With over 25 years of industry experience, NEORIS, part of the EPAM group, is committed to offering technical specialization career paths to our people. Our goal is to continue growing, and for that, we want you to join us and help us improve every day. We keep expanding our teams and are looking for professionals who share our culture and values: responsibility, collaboration and teamwork, creativity, and commitment. If you are eager to continuously learn, specialize, and work on cutting‑edge technology projects, we would love to hear from you. Our evaluation processes focus on professional experience, technical knowledge, personal motivations, and soft skills. We strongly believe in inclusion and equal employment opportunities. We are looking for: Principal AI Platform Engineer Key Responsibilities 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 performan

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