Descripción de la oferta
AI Platform Engineer – Spain – Remote with occasional visits to site - €530pd ¿Interesado en saber más sobre este trabajo? Desplácese hacia abajo y descubra qué habilidades, experiencia y cualificaciones académicas se necesitan. Contract until the end of the year €530pd Remote with occasional site visits, expenses will be paid for travel We seek a Principal AI Platform Engineer join our Enterprise AI Platforms and Technologies Team. The ideal candidate will have industry-relevant experience delivering at-scale Machine Learning/Data Science in the AWS cloud ecosystem or its competitors. You will be part of a collaborative team of multidisciplinary engineers and have the chance to create tools that will advance the standard of healthcare, improving the lives of millions of patients across the globe. As a Principal AI Platform Engineer interested in building complex systems, you will be responsible for inventing how we use technology, machine learning, and data to enable the productivity. You will help design, build, and deploy our next-generation platforms and tools at scale. Key Accountabilities Work closely with Enterprise architects to define the target architecture and roadmap for the enterprise Data/AI platform covering experimentation, training, feature management, model registry, CI/CD, serving, and observability. Ensure multi-tenant, multi-region, and high-availability designs with clear guardrails. Partner with product management to shape platform vision, backlogs, and OKRs. Establish golden paths, templates, and self-service experiences that reduce friction from ideation to industrialization. Own capacity planning and cost optimization for GPU/CPU workloads. Drive performance engineering for distributed training and inference and set standards for scalability and efficiency. Integrate with enterprise data platforms and orchestrators to support scalable pipelines, reproducible experiments, and governed access to datasets. Identity and secrets management, encryption, and vulnerability management. Partner with Cyber Security and Data Privacy to meet GxP and internal standards without hindering productivity. Drive reusable platform components, common services, and APIs that support multiple business units. Translate complex platform concepts for senior stakeholders; align solutions to business outcomes in R&D, Commercial, and Operations. Technical Leadership and Expertise Strong analytical and problem-solving skills to address challenges. Proven and creative technical leadership skills to drive detailed design and fact-based decision-making. Strong ability to create and communicate designs to engineers that are scalable and efficient AI platforms; implement and maintain the infrastructure and platforms that support the development and deployment of AI solutions. Experience in DevOps/MLOps/AIOps practices to streamline the development and deployment processes. Strong programming skills in Infrastructure as Code (e.g., Terraform, CloudFormation), AWS Services, collaborative software development, programming languages used in AI such as Python, proficiency in containerization technologies like Docker, etc.; and the ability to write clean, efficient, and maintainable code. Familiarity with big data technologies, including Apache Spark, for processing and analyzing large datasets. Understanding of security standard processes in AI systems and consistency to compliance standards. Willingness to stay updated with the latest advancements in AI technologies through continuous learning and professional development. Actively contributes to the continuous improvements/roadmaps of existing AI platforms. Candidate Knowledge, Skills, and Experience BE/MS/PhD in Computer Science, Engineering, or a related quantitative field. Demonstrable experience with AWS (or equivalent) across compute, storage, networking, IAM, and cost controls. Experience administering production EKS clusters; strong understanding of operators, storage classes, service mesh, and GPU workloads. Proven track record delivering platform software and automation in Python. Hands-on experience deploying and operating ML/DS infrastructure using Infrastructure as Code. Experience building model pipelines and lifecycle tooling to accelerate experimentation-to-production. Experience with LLM serving, RAG, vector databases, prompt safety, and token-aware scaling. Experience designing and operating agentic systems, including multi-agent orchestration, tool/action frameworks (e.g., function/tool calling), safety guardrails for autonomous actions, session/state management, and evaluation of agent reliability and cost/performance. Experience with internal security standards; GxP life sciences experience preferred. xcskxlj Soft Skills: Creative, collaborative, resilient, with excellent communication and the ability to influence technical and business stakeholders.
