Description

Your Opportunity

At Schwab, you're empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us "challenge the status quo" and transform the finance industry together.

We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location(s).

Schwab Data is advancing the next-generation roadmap for AI and data science platforms, enabling scalable, secure, and governed capabilities across multiple business domains. This includes expanding predictive analytics platforms and generative AI capabilities on Cloud, supporting use cases such as customer analytics, risk analytics, internal productivity, and operational decisioning.

As part of this evolution, we are scaling AI/ML platform and engineering capabilities on Cloud to support broader adoption. This includes standardizing platform architecture, enabling reusable development and deployment patterns, strengthening model lifecycle capabilities, and integrating platform services to support both predictive and generative AI workloads in a regulated environment.

We are seeking an Applied AI/ML Platform Services Principal to provide senior technical leadership across AI/ML platforms and engineering. This role will drive cross-platform architecture, define engineering standards, and enable scalable, production-grade AI capabilities. That role partners closely with platform engineering, AI/ML engineering, and data & enterprise architecture teams to align delivery, improve engineering maturity, and accelerate AI adoption.

Position Responsibilities:

AI/ML Platform Architecture & Strategy

• Define and drive the architecture for AI/ML platforms and services spanning predictive and generative AI domains
• Establish standardized, reusable platform patterns to support scalable, reliable, and governed AI workloads
• Lead integration strategies that connect AI/ML capabilities across the broader enterprise data ecosystem

AI/ML Engineering Standards & Enablement

• Define and implement AI/ML engineering best practices across development, deployment, and lifecycle management
• Enable consistent and effective use of platform capabilities for model development and evaluation
• Partner closely with engineering teams to improve platform reliability, scalability, and operational maturity

Cross-Functional Technical Leadership

• Serve as a senior technical authority across platform engineering, AI/ML engineering, and architecture teams
• Drive alignment on platform direction, priorities, and execution across multiple organizations
• Influence key technical decisions related to platform evolution and AI/ML engineering practices

Platform Adoption & Delivery Acceleration

• Enable onboarding and scaling of AI use cases through standardized platform capabilities
• Identify and remove technical or process bottlenecks impacting delivery velocity and scalability
• Support high-priority AI initiatives through hands-on technical leadership and guidance

Governance, Risk, and Compliance Alignment

• Ensure AI/ML platforms align with enterprise governance, risk, and regulatory requirements
• Drive consistent implementation of controls across the AI/ML lifecycle and platform services
• Partner with risk, compliance, and control functions to support compliant, transparent, and auditable AI usage

What you have

Required Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• 15+ years of experience in platform architecture/engineering, software engineering, or AI/ML engineering
• 5+ years operating at a Principal Engineer or equivalent senior technical leadership level
• Strong experience designing and scaling AI/ML platforms and services in cloud environments (GCP preferred)
• Hands-on experience with AI/ML platforms such as Vertex AI, Dataiku, SageMaker, or equivalent
• Deep understanding of the AI/ML lifecycle including model development, training, deployment, and monitoring
• Experience working within large-scale data ecosystems and integrating with data platforms
• Familiarity with distributed systems, platform architecture, and scalable service design
• Proven ability to define and implement engineering standards and platform patterns across teams
• Experience driving cross-functional technical alignment across multiple engineering groups
• Strong understanding of platform scalability, reliability, and operational excellence principles
• Demonstrated ability to reduce vendor dependency and build internal engineering capability

Preferred Qualifications:

• Experience in financial services or regulated environments
• Familiarity working within centralized data organizations (CDO structures)
• Experience supporting Data & AI platforms at scale
• Prior experience driving cloud-based platform expansion (GCP preferred)
• Strong background in cross-domain platform integration and architecture collaboration

In addition to the salary range, this role is also eligible for bonus or incentive opportunities.



Requisition #: 2026-121357

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Requirements

2026-121357