Senior Team Manager, Cloud Data & AI Platform Engineering

About the role

As a Senior Manager, Cloud Data & AI Platform Engineering, you will lead the strategy, engineering, and evolution of shared data and AI platforms that power enterprise analytics and AI at scale. You will shape how cloud-native platforms are designed, modernized, and operated—driving scalability, resiliency, and automation while enabling engineering teams and analytics users to deliver high-impact outcomes.

Responsibilities

• Lead the design, development, and operation of cloud-native data and AI platforms
• Drive the implementation of scalable, resilient, and automated cloud platforms
• Collaborate with security, risk, compliance, and business stakeholders to ensure platforms meet regulatory expectations
• Enable intelligent, AI-assisted platform experiences such as conversational analytics and developer productivity accelerators
• Influence enterprise-wide platform transformation by establishing engineering patterns, improving operational maturity, and integrating cloud automation and infrastructure as code

Requirements

• Proven experience designing and leading large-scale enterprise cloud platforms with a focus on scalability, resiliency, and high availability
• Experience with cloud technologies such as BigQuery, Kubernetes (GKE), Dataflow, Pub/Sub, Dataproc, Cloud Run, Cloud Functions, Cloud Storage, IAM, and observability tooling
• Strong understanding of platform engineering, site reliability engineering (SRE), service lifecycle management, and operational excellence
• Experience with Infrastructure as Code (e.g., Terraform), CI/CD enablement, automation frameworks, and reusable deployment patterns
• Experience supporting enterprise data, analytics, or AI/ML platforms, including solutions used by engineering and analytics teams
• Familiarity with generative AI concepts, LLM-enabled workflows, or AI-assisted engineering capabilities

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related technical field
• 10+ years of experience in cloud, platform, data, analytics, or AI engineering roles
• 5+ years of experience leading engineering teams or enterprise platform capabilities
• Strong expertise with Google Cloud Platform (GCP) and cloud-native engineering practices
• Experience with Infrastructure as Code (e.g., Terraform), CI/CD enablement, automation frameworks, and reusable deployment patterns
• Experience supporting enterprise data, analytics, or AI/ML platforms, including solutions used by engineering and analytics teams
• Familiarity with generative AI concepts, LLM-enabled workflows, or AI-assisted engineering capabilities
• Strong communication skills with the ability to connect technical solutions to business outcomes

Skills

• Strong expertise with Google Cloud Platform (GCP)
• Experience with cloud technologies such as BigQuery, Kubernetes (GKE), Dataflow, Pub/Sub, Dataproc, Cloud Run, Cloud Functions, Cloud Storage, IAM, and observability tooling
• Strong understanding of platform engineering, site reliability engineering (SRE), service lifecycle management, and operational excellence
• Experience with Infrastructure as Code (e.g., Terraform), CI/CD enablement, automation frameworks, and reusable deployment patterns
• Experience supporting enterprise data, analytics, or AI/ML platforms, including solutions used by engineering and analytics teams
• Familiarity with generative AI concepts, LLM-enabled workflows, or AI-assisted engineering capabilities
• Strong communication skills with the ability to connect technical solutions to business outcomes

Benefits

• 401(k) with company match and Employee stock purchase plan
• Paid time for vacation, volunteering, and 28-day sabbatical after every 5 years of service for eligible positions
• Paid parental leave and family building benefits
• Tuition reimbursement
• Health, dental, and vision insurance