Platform Engineer For Enterprise Ai Platforms

????????AstraZeneca develops life-changing medicines and uses data, analytics, AI, and modern engineering to support research, patient safety, and innovation across its global enterprise.Its AI Platforms and Technologies Team builds and maintains cloud-native infrastructure, vendor platforms, and enterprise AI and data science platforms.??????Design, implement, and manage AWS cloud infrastructure using Infrastructure as Code tools such as Terraform or AWS CloudFormation; Ensure platform reliability, scalability, and high availability across development, staging, and production environments; Design secure, compliant, and multi-tenant infrastructure aligned with enterprise security and governance standards; Evaluate, integrate, and optimize Domino, Databricks, Dataiku, and other vendor platforms for enterprise-scale use; Assess vendor features, develop proof-of-concepts, and evaluate business value, technical feasibility, and integration impact; Plan and execute approved vendor feature implementations with minimal production disruption; Serve as the primary technical liaison with vendor partners, managing escalations, roadmap discussions, implementation support, and feature alignment; Advise on adoption of current vendor innovations and capabilities; Design and implement integrations between AI platforms and enterprise data systems, including AWS S3, Snowflake, and other data warehouses; Integrate data governance and access control tools such as Immuta and Collibra with AI platforms; Build data pipelines and connectors while maintaining data lineage, quality, and security standards; Ensure seamless operation of the platform ecosystem for data scientists and engineers; Automate deployment activities using GitHub Actions, AWS CodePipeline, Jenkins, and ArgoCD; Develop and maintain pipelines for platform updates, vendor upgrades, and application deployments; Automate operational tasks, environment provisioning, configuration management, and infrastructure scaling using Python, Bash, or PowerShell; Implement automated testing, validation, and rollback strategies; Own assigned platform work packages from planning and design through implementation and deployment; Plan, estimate, and schedule work while identifying dependencies across platform components, vendors, and enterprise initiatives; Manage dependencies and coordinate across vendor partners, internal teams, and stakeholders; Communicate progress, risks, and blockers to the manager and stakeholders; Enable and maintain machine learning environments for scalable model training, hosting, and pipelines; Implement and manage observability tools such as Amazon CloudWatch, Prometheus/Grafana, and ELK; Support container orchestration environments using EKS, Kubernetes, ECS, or Fargate; Collaborate with security and compliance teams on IAM, encryption, logging, monitoring, and cost optimization; Ensure platform configurations and vendor integrations comply with security, data governance, and regulatory standards; Manage and publish curated infrastructure templates through AWS Service Catalogue and platform portals; Engage with AI scientists and engineers to understand their needs and translate them into platform capabilities; Provide technical guidance and support to platform users and gather feedback for roadmap improvements; Contribute to incident response, post-mortems, and continuous improvement of platform operations.??????????Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent professional experience; 5+ Years of hands-on experience with AWS cloud services, including compute, storage, networking, IAM, and cost controls; Strong experience with Terraform, AWS CDK, or CloudFormation; Proficiency in Linux system administration and networking fundamentals, including VPC design, security groups, and load balancing; Solid understanding of IAM policies, encryption, and security best practices; Experience with Docker and container orchestration using Kubernetes, preferably EKS, or ECS/Fargate; Hands-on experience with CI/CD tools and Git version control; 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, Dataiku, or other vendor platforms at scale; Background in Agile and platform-oriented delivery; 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; Experience integrating data platforms and warehouses such as AWS S3, Snowflake, and Redshift; Familiarity with data governance tools such as Immuta and Collibra; Understanding of data lineage, data quality, and secure data access patterns; Ability to rapidly learn new vendor platforms and tools; Strong troubleshooting and problem-solving skills; Excellent written and verbal communication skills, including the ability to explain complex technical concepts to diverse audiences; Collaborative mindset and ability to work across teams, vendors, and stakeholders; Ability to own work packages and drive them to completion with minimal supervision; Nice to have: Demonstrated knowledge of Databricks, Domino, Dataiku, or similar ML/AI vendor platforms.???????Continuous learning opportunities through hackathons, external partnerships, and professional development; Work with AI, cloud, vendor, and open-source technologies; Global, multidisciplinary engineering team and investment in digital transformation; In-person working averages a minimum of three days per week from the office; AstraZeneca supports diversity, equality of opportunity, and applicable work authorization and employment eligibility requirements.#J-*****-Ljbffr

Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent professional experience; 5+ Years of hands-on experience with AWS cloud services, including compute, storage, networking, IAM, and cost controls; Strong experience with Terraform, AWS CDK, or CloudFormation; Proficiency in Linux system administration and networking fundamentals, including VPC design, security groups, and load balancing; Solid understanding of IAM policies, encryption, and security best practices; Experience with Docker and container orchestration using Kubernetes, preferably EKS, or ECS/Fargate; Hands-on experience with CI/CD tools and Git version control; 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, Dataiku, or other vendor platforms at scale; Background in Agile and platform-oriented delivery; 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; Experience integrating data platforms and warehouses such as AWS S3, Snowflake, and Redshift; Familiarity with data governance tools such as Immuta and Collibra; Understanding of data lineage, data quality, and secure data access patterns; Ability to rapidly learn new vendor platforms and tools; Strong troubleshooting and problem-solving skills; Excellent written and verbal communication skills, including the ability to explain complex technical concepts to diverse audiences; Collaborative mindset and ability to work across teams, vendors, and stakeholders; Ability to own work packages and drive them to completion with minimal supervision; Nice to have: Demonstrated knowledge of Databricks, Domino, Dataiku, or similar ML/AI vendor platforms. ??????? Continuous learning opportunities through hackathons, external partnerships, and professional development; Work with AI, cloud, vendor, and open-source technologies; Global, multidisciplinary engineering team and investment in digital transformation; In-person working averages a minimum of three days per week from the office; AstraZeneca supports diversity, equality of opportunity, and applicable work authorization and employment eligibility requirements. #J-*****-Ljbffr