22 hours ago
Remote, Germany +6 moreStaff+
Responsibilities
- Define technical strategy for AI/ML platform infrastructure supporting generative AI applications, LLM integrations, model routing, and enterprise AI services.
- Architect, build, and operate scalable AWS cloud platforms across containerized, serverless, networking, storage, observability, and security services.
- Establish reusable infrastructure patterns with CloudFormation, Helm, and Terraform for multi-environment and multi-region deployments.
- Lead CI/CD architecture, including reusable workflows, automated quality gates, deployment promotion, environment approvals, and cloud authentication.
- Design observability using dashboards, logs, alarms, Prometheus/Grafana, OpenSearch, Langfuse, and LLM-specific operational metrics.
- Build platform capabilities for GenAI workloads, including model availability monitoring.
- Improve deployment reliability, rollback strategies, health checks, autoscaling, load testing, and runtime performance.
- Define infrastructure security and compliance practices covering IAM permission boundaries, secrets management, secret scanning, audit logging, tagging, and change management.
- Lead cost optimization, capacity planning, environment standardization, and operational resilience.
- Mentor engineers, review architecture and infrastructure designs, and influence platform engineering practices across teams.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related technical field, or equivalent practical experience.
- At least 7 years of experience in DevOps, platform engineering, cloud infrastructure, site reliability engineering, or software engineering roles.
- Strong hands-on experience with AWS, Azure, or GCP infrastructure and services.
- Experience designing and operating production systems on Kubernetes, ECS/Fargate, or comparable container orchestration platforms.
- Proficiency with infrastructure-as-code tools such as CloudFormation, Terraform, or Helm.
- Strong CI/CD experience with GitHub Actions or similar platforms, including reusable workflows, automated testing, deployment gates, and cloud authentication.
- Experience building and operating observability solutions with CloudWatch, Prometheus/Grafana, OpenSearch, or similar tools.
- Strong understanding of cloud security, IAM, secrets management, least-privilege access, audit logging, and compliance requirements.
- Experience supporting distributed systems, microservices, APIs, asynchronous workloads, and multi-environment deployments.
- Demonstrated ability to lead technical design, mentor engineers, and influence engineering practices across teams.
- Preferred experience with AI/ML or generative AI platforms, LLM gateways, model routing, prompt observability, token metering, or model failover.
- Preferred experience in regulated enterprise environments and with multi-account, multi-region AWS architectures, enterprise governance, cost optimization, autoscaling, capacity planning, or cloud budget monitoring.
- Experience with load testing and performance validation using Locust or comparable frameworks is preferred.
- Strong Python or scripting skills for platform automation, operational tooling, and CI/CD extensions are preferred.
Benefits
- Remote work location assignment.
- Pfizer is an equal opportunity employer with diversity, inclusion, accessibility, and reasonable accommodation commitments.
Tech Stack
Amazon DynamoDBAWSAzureDockerGitHub ActionsGoogle Cloud PlatformGrafanaHelmKubernetesPrometheusPythonTerraform
Categories
About Pfizer
Pfizer is a publicly traded biopharmaceutical company that discovers, develops, manufactures, and markets prescription medicines and vaccines for patients, healthcare systems, and governments worldwide. Its portfolio spans oncology, vaccines, immunology, and rare disease, with products such as the COVID-19 vaccine (with BioNTech) and the antiviral Paxlovid. Founded in 1849 and headquartered in New York City, Pfizer operates globally under the ticker PFE on the NYSE.