Staff platform engineer, ai/ml infrastructure
Pubblicato il 22-09-2026 - Pfizer in Roma
Staff 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. 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, Dynamo DB, S3, Open Search, Secrets Manager, Cloud Watch, ALB, and MWAA. Establish reusable infrastructure patterns using Cloud Formation, Helm, and Terraform to supportreliable multi-environment and multi-region deployments. Lead CI/CD architecture using Git Hub Actions, reusable workflows, OIDC-based AWSauthentication, automated quality gates, deployment promotion, and environment approvals.
Design and improve observability across AI platforms, including Cloud Watch dashboards, logs,alarms, Prometheus/Grafana, Open Search, Langfuse, and LLM-specific operational metrics. Build platform capabilities for Gen AI 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 security and compliance practices for infrastructure, including IAM permissionboundaries, Secrets Manager usage, secret scanning, audit logging, tagging standards, andchange-management controls. Provide technical leadership for cost optimization, capacity planning, environment standardization,and operational resilience across development, test, production, and sandbox environments. Mentor engineers,
review architecture and infrastructure designs, and influence platformengineering practices across teams.
Bachelor's degree in Computer Science, Engineering, Information Technology, or a relatedtechnical field, or equivalent practical experience. 7+ years of experience in Dev Ops, platform engineering, cloud infrastructure, site reliabilityengineering, or software engineering roles. Strong 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, orcomparable container orchestration platforms. Proficiency with infrastructure-as-code, especially Cloud Formation, Terraform, Helm, or similartooling. Strong CI/CD experience with Git Hub Actions or similar platforms, including reusable workflows,automated testing, deployment gates, and cloud authentication.
Experience building and operating observability solutions using Cloud Watch, Prometheus/Grafana, Open Search, or similar tools. Strong understanding of cloud security practices, IAM, secrets management, least-privilegeaccess, audit logging, and compliance requirements.
Experience supporting distributed systems, microservices, APIs, asynchronous workloads, andmulti-environment deployments. Demonstrated ability to lead technical design, mentor engineers, and influence engineeringpractices across teams.
Experience supporting AI/ML or generative AI platforms, including LLM gateways, model routing,prompt observability, token metering, or model failover.
Experience operating platforms in regulated enterprise environments, ideally healthcare,pharmaceutical, finance, or life sciences.
Experience with multi-account, multi-region AWS architectures and enterprise governancepatterns.
Experience with cost optimization, autoscaling strategies, capacity planning, and cloud budgetmonitoring.
Experience with load testing and performance validation using tools such as Locust or comparableframeworks.
Strong
Python or scripting skills for platform automation, operational tooling, and CI/CD extensions. Ability to communicate complex technical decisions clearly to engineering,
security, operations,and leadership audiences.
Technical Environment
This role works across a modern AI platform ecosystem including: Cloud: AWS EKS, ECS Fargate, Lambda, Dynamo DB, S3, Open Search, Cloud Watch, Secrets Manager, ALB, VPC, IAM Infrastructure-as-Code: Cloud Formation, Helm, Terraform CI/CD: Git Hub Actions, reusable workflows, OIDC federation, environment approvals, automatedrelease promotion AI/ML Platform: AWS Bedrock, Azure Open AI, Lite LLM, Langfuse Observability: Cloud Watch dashboards and alarms, Prometheus, Grafana, Open Search, Langfuse,custom metrics Security & Governance: IAM permission boundaries, secret scanning, audit logging, taggingcompliance, change-management automation Engineering Practices: Docker, Python, pre-commit, automated testing, load testing, code qualitygates, monorepo service standards Leadership Expectations As a J090 Staff-level engineer, this role is expected to operate beyond individual delivery. The engineerwill identify systemic platform gaps, define technical direction, create reusable standards, and raiseengineering maturity across multiple teams. The engineer should beable to balance hands-on implementation with architectural leadership, guide teams through ambiguoustechnical decisions, and build platform capabilities that make AI product teams faster, safer, and morereliable.
Remote
Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates. En tant qu'employeur, Pfizer s'engage à valoriser la diversité et l'inclusion sous toutes ses formes. Handicap & Inclusion Notre mission est de libérer le potentiel de nos collaborateurs et nous sommes fiers d'être un employeur inclusif pour les personnes handicapées, garantissant ainsi l'égalité des chances en matière d'emploi pour tous les candidats.
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