Role Overview
We are looking for an experienced Senior AI Infrastructure & Platform Engineer to support the reliability, operation, and continuous improvement of enterprise AI and data platforms.
This role combines AI infrastructure, cloud/platform engineering, observability, and production support, with a strong focus on ensuring platform stability, operational readiness, and scalability. The engineer will work closely with China and global technology teams to support production AI capabilities and drive continuous platform improvement.
Key Responsibilities
- AI Infrastructure & Platform Operations
Operate and maintain enterprise AI and data platform services across cloud, Kubernetes, databases, data platforms, and AI supporting services, ensuring availability, performance, capacity, security, and operational readiness. - Monitoring & Reliability Engineering
Build and improve monitoring, observability, alerting, and health-check capabilities using tools such as Grafana, CloudWatch, and Langfuse. Proactively identify reliability and performance risks and drive preventive improvements. - L2/L3 Technical Support & Problem Solving
Troubleshoot complex production issues across infrastructure, application, data, API, database, and integration layers. Conduct root cause analysis and drive permanent remediation for recurring or high-impact issues. - Platform Engineering & Continuous Improvement
Support platform configuration, integration, performance tuning, patching, upgrades, releases, and technical enhancements. Drive automation and engineering improvements to reduce manual operational effort. - Production Readiness & Collaboration
Partner with AI/Data Engineering, Product, Infrastructure, Global teams, and external technology partners to onboard new AI capabilities, manage production changes, maintain operational documentation, and ensure effective transition into BAU.
Qualifications & Technical Skills
Required
- 6+ years of experience in Platform Engineering, Cloud Infrastructure, DevOps/SRE, Data Platform, AI Platform, or enterprise production support.
- Strong hands-on experience with AWS and Kubernetes/EKS.
- Experience with monitoring and observability, such as Grafana, CloudWatch, application logs, metrics, and tracing.
- Solid knowledge of Linux, networking, databases/SQL, APIs, and distributed applications.
- Strong troubleshooting skills across infrastructure, platform, application, data, and integration layers.
- Experience with scripting or automation using Python, Shell/Bash, SQL, or similar technologies.
- Experience supporting complex, business-critical production environments.
- Excellent written and verbal English communication skills, with the ability to independently communicate, troubleshoot, and collaborate with global engineering and technology teams.
Preferred
- Experience supporting AI/ML or GenAI platforms in production.
- Experience with Langfuse or other LLM observability/tracing solutions.
- Experience with Neo4j or other graph databases.
- Experience with Collibra, Dataiku, Redshift/PostgreSQL, or similar enterprise data platforms.
- Familiarity with Incident, Problem, Change, Release, DR, and production readiness processes.
- Experience in pharmaceutical, healthcare, or other regulated industries is a plus.
Work Location Assignment: On Premise
Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.
To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers.
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