Associate Principal AI Platform Enginee

Associate Principal AI Platform Enginee

Barcelona

Categoría: DevOps

Salario: ~

Empresa: AstraZeneca

Estudios:

Experiencia: Más de 5 años

Tipo de contrato: Indefinido

Jornada: Jornada completa

Fecha: 23/08/2026

Descripción: 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 AstraZeneca´s 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 platform´s operational excellence

Required Skills & Qualifications
Education
- Bachelor´s 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 secure data access patterns

Vendor & Industry Knowledge
- Quick learner with ability to rapidly acquire knowledge of new vendor platforms and tools
- Awareness of current industry trends and innovations in ML/AI platforms and data engineering
- Familiarity with vendor products in the ML/AI space (experience with or demonstrated knowledge of Databricks, Domino, Dataiku, or similar platforms is a plus)

Soft Skills
- Strong troubleshooting and problem-solving skills
- Excellent written and verbal communication skills, with ability to communicate complex technical concepts to diverse audiences
- Collaborative mindset with ability to work effectively across teams, vendors, and stakeholders
- Ability to take ownership of work packages and drive them to completion with minimal supervision

Why Join Us?
- Work at the forefront of AI innovation in healthcare, supporting life-changing medicines and patient outcomes
- Own meaningful platform work packages and see your contributions directly impact AI scientists and engineers globally
- Collaborate with a passionate, multidisciplinary engineering team and learn from world-class technical leaders
- Influence platform strategy and architecture in partnership with your manager and peers
- Work with cutting-edge cloud, vendor, and open-source technologies; shape how we adopt innovation
- Continuous learning opportunities through hackathons, external partnerships, and professional development
- Excellent work culture, global team, and strong investment in digital transformation across AstraZeneca

Publicado 24-08-2026

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