🇪🇸 Barcelona, Spain
Associate Principal AI Platform Enginee
AstraZeneca
TecnoempleoleadEnglish-friendlyonsite
About AstraZeneca AstraZeneca offers the chance to disrupt an industry while working on technology that directly supports life-changing medicines. Here data analytics AI and modern engineering come together with science to unlock new possibilities for patients. The environment is dynamic and hands-on experiment with leading-edge platforms shape new ways of working at scale learn continuously through collaboration with diverse experts hackathons and external partnerships and see the impact of decisions across a truly global enterprise backed by strong investment in digital transformation. About the AI Platforms Team The Enterprise AI Platforms and Technologies Team is responsible for building developing and maintaining the AI platforms that power AstraZenecas ambition to use AI in every step of the value chain-from discovering new compounds to patient safety systems. We are at the forefront of innovation ensuring we introduce the latest and best technology quickly in a scalable manner. Our mission is to empower AI scientists and engineers across the enterprise by managing all infrastructure and platform operations. We build develop and maintain - Cloud Native infrastructure and automation - Vendor platforms including Domino Databricks and Dataiku - Home-grown AI and data science platforms tailored to our enterprise needs About the Role As an Associate Principal AI Platform Engineer you will drive individual work packages within our platform ecosystem taking ownership of specific initiatives and ensuring their successful delivery. You will work closely with vendor partners (Domino Databricks Dataiku etc.) internal stakeholders and our key customer teams (AI scientists and engineers) to design implement and optimize platform capabilities. You will report to the Principal AI Platform Engineer and/or Product Owner who owns the overall platform strategy and vision. Your role is critical in translating that vision into scalable reliable and user-centric platform components that accelerate research and drive innovation at scale. Key Responsibilities Platform Architecture Design - Design implement and manage cloud infrastructure on AWS using Infrastructure as Code (IaC) tools such as Terraform or AWS CloudFormation - Ensure platform reliability scalability and high availability across development staging and production environments - Design multi-tenant secure and compliant infrastructure that meets enterprise security and governance standards Vendor Integration Feature Assessment - Evaluate integrate and optimize vendor platforms (Domino Databricks Dataiku etc.) for enterprise use at scale - Assess new vendor features and capabilities develop proof-of-concepts and evaluate business value technical feasibility and integration impact - Plan and execute the implementation of approved vendor features ensuring minimal disruption to production environments and seamless integration with existing platform components - Serve as the primary technical contact and liaison with vendor partners managing technical escalations roadmap discussions implementation support and feature roadmap alignment - Stay current with vendor product innovations and advise on adoption of cutting-edge features and capabilities to ensure AstraZeneca remains at the forefront of technology Platform Ecosystem Integration - Design and implement seamless integrations between AI platforms and enterprise data systems including AWS S3 Snowflake and other data warehouses - Integrate data governance and access control tools (Immuta Collibra etc.) with AI platforms to ensure secure compliant access to datasets - Build data pipelines and connectors that enable smooth data flow between platforms while maintaining data lineage quality and security standards - Ensure the platform ecosystem operates as a seamless integrated whole minimizing friction for data scientists and engineers when accessing data and deploying models Deployment Automation Operational Excellence - Automate all deployment activities across the platform ecosystem using CI/CD tools (GitHub Actions AWS CodePipeline Jenkins ArgoCD) to ensure rapid reliable and repeatable deployments - Develop and maintain deployment pipelines for platform updates vendor platform upgrades and application deployments to minimize manual effort and reduce deployment risk - Automate operational tasks environment provisioning configuration management and infrastructure scaling using scripting languages such as Python Bash or PowerShell - Implement automated testing validation and rollback strategies to ensure high-quality deployments and rapid incident recovery Work Package Ownership Execution - Take full ownership of assigned platform work packages from planning and design through implementation and deployment - Plan estimate and schedule work identify dependencies with other platform components vendor deliverables and enterprise initiatives - Manage dependencies and coordinate across vendor partners internal teams and key stakeholder groups - Communicate progress risks and blockers transparently to your manager and stakeholders Platform Operations DevOps - Enable and maintain machine learning environments (Databricks Domino etc.) for scalable ML model training hosting and pipelines - Implement and manage observability tools like Amazon CloudWatch Prometheus/Grafana or ELK for monitoring alerting and platform insights - Support container orchestration environments using EKS (Kubernetes) ECS or Fargate Security Compliance Governance - Collaborate with security and compliance teams to implement best practices around IAM encryption logging monitoring and cost optimization - Ensure platform configurations and vendor integrations comply with enterprise security data governance and regulatory standards - Manage and publish curated infrastructure templates through AWS Service Catalogue and platform portals to enable consistent and compliant provisioning Stakeholder Engagement Support - Engage with key customer teams (AI scientists and engineers) to understand their needs and translate them into platform capabilities - Provide technical guidance and support to platform users gather feedback to inform platform roadmap and improvements - Contribute to incident response post-mortems and continuous improvement of the platforms operational excellence Required Skills Qualifications Education - Bachelors degree in Computer Science Engineering or related field (or equivalent professional experience) Platform Engineering - 5+ years of hands-on experience with AWS cloud services (compute storage networking IAM cost controls) - Strong experience with Terraform AWS CDK or CloudFormation - Proficiency in Linux system administration and networking fundamentals (VPC design security groups load balancing) - Solid understanding of IAM policies encryption and security best practices - Experience with Docker and container orchestration using Kubernetes (EKS preferred) or ECS/Fargate - Hands-on experience with CI/CD tools (GitHub Actions Jenkins ArgoCD AWS CodePipeline) and version control (Git) - Experience supporting AI/ML workloads - Hands-on experience with serverless technologies - Experience with LLM RAG architectures vector databases and generative AI platforms - Experience administering or deploying Domino Databricks or Dataiku platforms or other vendor platforms at scale. - Background in Agile with platform or product-focused delivery experience Software Development Scripting - Proficiency in Python Bash or PowerShell for automation and scripting - Ability to write clean efficient and maintainable infrastructure code - Experience with monitoring logging and alerting systems (CloudWatch Prometheus/Grafana ELK) Data Integration Data Governance - Experience integrating data platforms and data warehouses (e.g. AWS S3 Snowflake Redshift) - Familiarity with data governance tools and platforms (e.g. Immuta Collibra or similar solutions) - Understanding of data lineage data quality and seSourced from Tecnoempleo. 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