Pfizer
Pharmaceutical
StaffPlatformEngineer,AI/MLInfrastructure
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optimal for Staff candidates.
“Staff Platform Engineer, AI/ML Infrastructure at Pfizer. Skills: AI/ML Infrastructure, Cloud Platforms, Generative AI, Kubernetes. Define technical strategy for AI/ML platform infrastructure. Architect scalable cloud platforms using AWS services”
Industry & Context.
Root cause analysis
What They're Looking For.
Must Have
Bachelor's degree in Computer Science, Engineering, Information Technology, or a related technical field, or equivalent practical experience, 7+ years of experience in DevOps, platform engineering, cloud infrastructure, site reliability engineering, or software engineering roles, hands-on experience with AWS/Azure/GCP infrastructure and services, including container, serverless, networking, storage, observability, and security services, Experience designing and operating production systems on Kubernetes, ECS/Fargate, or comparable container orchestration platforms, Proficiency with infrastructure-as-code, especially CloudFormation, Terraform, Helm, or similar tooling, 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 using CloudWatch, Prometheus/Grafana, OpenSearch, or similar tools, understanding of cloud security practices, 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
Nice to Have
Experience supporting AI/ML or generative AI platforms, Experience operating platforms in regulated enterprise environments, Experience with multi-account, multi-region AWS architectures, Experience with cost optimization, autoscaling strategies, capacity planning, and cloud budget monitoring, Experience with load testing and performance validation, Python or scripting skills for platform automation, Ability to communicate complex technical decisions clearly
What You'll Do.
Define technical strategy for AI/ML platform infrastructure
Architect scalable cloud platforms using AWS services
Build scalable cloud platforms using AWS services
Operate scalable cloud platforms using AWS services
Establish reusable infrastructure patterns
Lead CI/CD architecture
Design observability across AI platforms
Improve observability across AI platforms
Build platform capabilities for GenAI workloads
Monitor model availability
Improve deployment reliability
Improve rollback strategies
Improve health checks
Improve runtime performance
Define security and compliance practices
Enforce security and compliance practices
Provide technical leadership for cost optimization
Provide technical leadership for capacity planning
Provide technical leadership for environment standardization
Provide technical leadership for operational resilience
Review architecture designs
Review infrastructure designs
Influence platform engineering practices
How You'll Work.
Team & Collaboration
Partnering with software engineering; Partnering with AI engineering; Partnering with security; Partnering with operations teams; Cross-functional teams
Communication Scope
Technical decisions
Process & Methodology
Agile
Full Job Description
**Staf****f Platform Engineer, AI/ML Infrastructure** Department:AI Software & Operations **Role Summary** The Staff Platform Engineer, AI/ML Infrastructure will provide technical leadership for thecloud platforms, deployment systems, and operational foundations that power enterprise-scalegenerative AI applications. This role will define and evolve the infrastructure architecture for AI/ML platforms running across AWS,Kubernetes, serverless, and containerized environments. The engineer will lead platform standards forreliability, scalability, observability, CI/CD, security, and developer enablement, while partnering closelywith software engineering, AI engineering, security, and operations teams. The ideal candidate combines deep hands-on cloud engineering experience with staff-level technicalinfluence. They are comfortable designing infrastructure patterns, writing infrastructure-as-code,improving delivery pipelines, mentoring engineers, and making architectural decisions that raise theoperational maturity of AI platforms across multiple teams. **Key Responsibilities** Define and drive the technical strategy for AI/ML platform infrastructure supporting generative AIapplications, LLM integrations, model routing, and enterprise AI services. Architect, build, and operate scalable cloud platforms using AWS services such as EKS, ECSFargate, Lambda, DynamoDB, S3, OpenSearch, Secrets Manager, CloudWatch, ALB, and MWAA. Establish reusable infrastructure patterns using CloudFormation, Helm, and Terraform to supportreliable multi-environment and multi-region deployments. Lead CI/CD architecture using GitHub Actions, reusable workflows, OIDC-based AWSauthentication, automated quality gates, deployment promotion, and environment approvals. Design and improve observability across AI platforms, including CloudWatch dashboards, logs,alarms, Prometheus/Grafana, OpenSearch, Langfuse, and LLM-specific operational metrics. Build platform capabilities for GenAI workloads, including mo
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