platform engineer for generative AI platforms

Pfizer is a pharmaceutical manufacturing company that develops medicines and serves patients and communities worldwide.

• Define and drive the technical strategy for AI/ML platform infrastructure supporting generative AI applications, LLM integrations, model routing, and enterprise AI services;
• Architect, build, and operate scalable cloud platforms using AWS services;
• Establish reusable infrastructure patterns for reliable multi-environment and multi-region deployments;
• Lead CI/CD architecture with reusable workflows, automated quality gates, deployment promotion, and environment approvals;
• Design and improve observability across AI platforms, including LLM-specific operational metrics;
• Build platform capabilities for GenAI workloads, including model availability monitoring;
• Partner with software engineering teams to improve deployment reliability, rollback strategies, health checks, autoscaling, load testing, and runtime performance;
• Define and enforce infrastructure security and compliance practices;
• Provide technical leadership for cost optimization, capacity planning, environment standardization, and operational resilience;
• Mentor engineers, review architecture and infrastructure designs, and influence platform engineering practices across teams.

• 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;
• Strong hands-on experience with AWS/Azure/GCP infrastructure and 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;
• Strong CI/CD experience with GitHub Actions or similar platforms;
• Experience building and operating observability solutions;
• Strong 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 in regulated enterprise environments, multi-account and multi-region AWS architectures, cost optimization, autoscaling, capacity planning, cloud budget monitoring, load testing, strong Python or scripting skills, clear communication of complex technical decisions.

• Remote work location assignment;
• Pay information will be shared during the first interview for secondary posting locations where pay transparency regulations apply;
• Equal employment opportunity and inclusive workplace.