Staff Platform Engineer, AI/ML Infrastructure

Biopharma Careers

Paris

Sur place

EUR 110 000 - 165 000

Plein temps

Il y a 5 jours
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Résumé du poste

Biopharma Careers is seeking a Staff Platform Engineer, AI/ML Infrastructure to lead cloud platforms powering enterprise AI apps. You will define infrastructure patterns, drive CI/CD, and ensure security and observability across AWS, Kubernetes, serverless, and containers.

Partner with software, AI, security and operations teams to raise platform maturity. The ideal candidate brings hands-on cloud engineering experience and staff-level influence, mentoring engineers and shaping architectural

Qualifications

  • Bachelor's degree in CS/Engineering or equivalent practical experience.
  • 7+ years in DevOps, platform engineering, or cloud infra roles.
  • Hands-on AWS/Azure/GCP experience with container/serverless stacks.
  • Proficient in infrastructure-as-code and CI/CD pipelines.
  • Strong security, observability, and cost-optimization skills.

Responsabilités

  • Define strategy for AI/ML platform infrastructure across AWS and Kubernetes.
  • Architect and operate scalable cloud platforms and CI/CD pipelines.
  • Lead reliability, observability, and security practices for platforms.
  • Mentor engineers and drive architectural decisions across teams.
  • Collaborate with software, AI, security, and ops teams to raise maturity.

Connaissances

Leadership
Mentoring
DevOps
Cloud engineering
CI/CD
Python
Communication
Automation

Formation

Bachelor's degree in CS/Engineering or related

Outils

Terraform
CloudFormation
Helm
Terraform
GitHub Actions
Kubernetes
OpenSearch
Langfuse
AWS (EKS, ECS, Fargate)

Description du poste

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.

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 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.
Basic Qualifications
  • Bachelor’s degree in Computer Science, Engineering, Information Technology, or a relatedtechnical field, or equivalent practical experience.
  • 7+ years of experience in DevOps, 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 CloudFormation, Terraform, Helm, or similartooling.
  • 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 using CloudWatch, Prometheus/Grafana,OpenSearch, 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.
Preferred Qualifications
  • 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
  • Cloud: AWS EKS, ECS Fargate, Lambda, DynamoDB, S3, OpenSearch, CloudWatch, SecretsManager, ALB, VPC, IAM
  • Infrastructure-as-Code: CloudFormation, Helm, Terraform
  • CI/CD: GitHub Actions, reusable workflows, OIDC federation, environment approvals, automatedrelease promotion
  • AI/ML Platform: AWS Bedrock, Azure OpenAI, LiteLLM, Langfuse
  • Observability: CloudWatch dashboards and alarms, Prometheus, Grafana, OpenSearch, 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.

Success in this role requires strong judgement, ownership, and communication. The engineer should be able to balance hands‑on implementation with architectural leadership, guide teams through ambiguous technical decisions, and build platform capabilities that make AI product teams faster, safer, and more reliable.

Work location assignment : Remote

This role is posted in multiple locations. If you are applying for the role in an secondary job posting location where pay transparency regulations apply, your Talent Advisor will share the local pay information with you during the first interview.

Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.

Égalité des chances & Emploi

Nous croyons que des équipes diversifiées et inclusives sont essentielles à la réussite d'une entreprise. En tant qu'employeur, Pfizer s'engage à valoriser la diversité et l’inclusion sous toutes ses formes. Cette diversité se reflète également à travers les patients et les communautés que nous servons. Ensemble, continuons à bâtir une culture qui encourage, soutient et responsabilise nos employés.

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. Nous vous encourageons à donner le meilleur de vous-même en sachant que nous apporterons tous les ajustements raisonnables pour soutenir votre candidature et votre carrière future. Votre expérience avec Pfizer commence ici!

Pfizer endeavors to make www.pfizer.com/careers accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email disabilityrecruitment@pfizer.com. This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process and/or interviewing. Requests for any other reason will not be returned.

Pour mieux comprendre les usages autorisés et interdits de l’intelligence artificielle tout au long du processus de recrutement, nous vous invitons à consulter nos bonnes pratiques dédiées à l’utilisation de l’IA par les candidats sur Pfizer Careers .

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