Staff Platform Engineer, Ai/Ml Infrastructure
Pubblicato il 02-10-2026 - Pfizer in Milano
In this role you will provide technical leadership for Pfizer’s AI/ML infrastructure, shaping cloud platforms and deployment foundations to power enterprise-scale generative AI apps. You will define patterns and standards across AWS/Kubernetes/serverless environments, focusing on reliability, scalability, observability, CI/CD, security, and developer enablement. You will collaborate with software, AI engineering, security, and operations teams to raise platform maturity. This is a hands-on, architecturally influential position with a strong emphasis on cross-team impact and platform-wide consistency.
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 such as EKS, ECS Fargate, Lambda, DynamoDB, S3, OpenSearch, Secrets Manager, CloudWatch, ALB, and MWAA
Establish reusable infrastructure patterns using CloudFormation, Helm, and Terraform for multi-environment/multi-region deployments
Lead CI/CD architecture with GitHub Actions, reusable workflows, OIDC-based AWS authentication, automated quality gates, deployment promotion, and environment approvals
Design and improve observability across AI platforms (CloudWatch, logs, Prometheus/Grafana, OpenSearch, Langfuse, and LLm metrics); build GenAI workload monitoring
Partner with software engineering teams to improve deployment reliability, rollback strategies, health checks, autoscaling, load testing, and runtime performance
Define and enforce security/compliance practices for infrastructure (IAM boundaries, Secrets Manager, secret scanning, audit logging, tagging, change-management)
Provide technical leadership for cost optimization, capacity planning, environment standardization, and resilience across environments
Mentor engineers, review architecture and infrastructure designs, influence platform engineering practices across team