Jobs / AstraZeneca
Senior Cloud Platform Engineer (AWS), AI Infrastructure - Evinova
AstraZeneca · Gaithersburg, MD, United States
Gaithersburg, MD, United StatesExp: 4+ yrs145,000-185,000 USD/yearlyHybrid
Remuneration
145,000-185,000 USD/yearly
Location
Gaithersburg, MD, United States
Visa sponsorship
Not specified
Job summary
The Senior Cloud Platform Engineer role is responsible for designing, building, and operating AWS infrastructure for Generative AI applications in a regulated pharmaceutical environment. Key responsibilities include writing AWS CDK in TypeScript and/or Python, managing containerized workloads with Amazon ECS, and establishing CI/CD workflows to support AI Engineers and Data Scientists in deploying reliable production services.
Benefits
401(k) planPaid vacation and holidaysPaid leavesHealth benefits including medical, prescription drug, dental, and vision coverag
Qualifications
- Minimum of 4 years of hands-on experience in a platform engineering, infrastructure, site reliability engineering (SRE) or DevOps role.
- Deep hands-on AWS cloud engineering experience, including designing, deploying and operating production cloud-native infrastructure.
- Strong experience with AWS services such as Bedrock, ECS, IAM, VPC, load balancing, S3, CloudWatch, Secrets Manager and related services.
- Strong hands-on experience with IaC. AWS CDK using Python and/or TypeScript is preferred.
- Strong experience with Docker and Amazon ECS.
- Experience designing and maintaining CI/CD and/or GitOps pipelines for production cloud workloads.
Responsibilities
- Design, build and operate scalable AWS cloud platform capabilities for production ML/AI and Generative AI workloads.
- Create reusable infrastructure, tooling and deployment patterns that enable AI Engineers and Data Scientists to independently deploy and operate their applications.
- Write and maintain AWS IaC primarily AWS CDK in TypeScript and/or Python.
- Build and operate containerized workloads using Amazon ECS.
- Develop reusable platform capabilities across compute, networking, IAM, secrets management, storage, model access and workload isolation.
- Build and maintain CI/CD and GitOps workflows that enable safe, automated and repeatable deployments across environments.
- Partner with engineers and Data Scientists to transition prototypes and research workloads into resilient, production-grade services.
Skills
AWSAWS CDKCloudWatchDatadogDockerECSEKSIAMKubernetesOpenTelemetryPrometheusPythonS3Secrets ManagerSplunkTerraformTypeScript
Relocation
No