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.

Treasury plays a critical role in safeguarding the company's financial health, managing liquidity, cash flow, funding, and risk across the enterprise. Through an integrated risk-stripe approach spanning market, liquidity, and capital risk, Treasury actively manages the firm's balance sheet to support sustainable business growth. In parallel, Treasury operates deeply embedded cash management and settlement functions that ensure daily obligations are met, while owning fund transfer pricing capabilities that enable the businesses to accurately attribute profitability

As Treasury continues to modernize, we are investing heavily in data, cloud platforms, and AI to elevate analyst productivity, decision-making speed, and analytical depth. This role sits at the center of that transformation.

The Senior Manager, Treasury Cloud & AI Platforms will lead the design and evolution of cloud-native data and AI capabilities that directly power Treasury analyst workflows. This role is responsible for building the technical foundation that enables advanced analytics, data products, and AI-assisted insights across Treasury.

What you have

Required Qualifications

• 8+ years of experience in software, data, or platform engineering
• Strong hands-on experience with cloud-based technologies, preferably GCP
• Advanced proficiency in Python
• Demonstrated experience with open-source data and AI tooling
• Strong background in data engineering and building data systems
• Experience implementing CI/CD, DevOps, and production operations
• Working knowledge of modern analytics and AI stacks, including:
  
• 
  dbt, dlt, DuckDB
• Vector search / embeddings
• LLM-based systems
  

What you'll do:

This is a hands-on technical leadership role for someone who is equally comfortable designing cloud-based platforms, working with open-source tooling, and partnering with Treasury stakeholders to operationalize AI.

You will:

• Build and scale cloud-native data and AI platforms on GCP
• Enable Treasury analysts through LLMs, vector search, and AI tooling
• Establish modern data engineering and DevOps practices
• Translate analytical and business needs into production-grade systems
  

The role contributes directly to embedding AI into day-to-day Treasury workflows.

Key Responsibilities

Cloud & Platform Engineering

• Architect, build, and operate cloud-native platforms on GCP
• Own infrastructure patterns for data, analytics, and AI services
• Ensure platforms are secure, scalable, observable, and resilient
  

Data Engineering & Analytics Enablement

• Design and maintain modern data pipelines and data models
• Strong software engineering skills, including experience building services and APIs using at least one modern programming language (such as Python, C#, or Java).
• Build analytical systems using tools such as dbt, dlt, DuckDB, and Cloud-native storage and compute
• Enable consistent, trusted data access for Treasury analytics
  

AI & Advanced Analytics

• Enable AI-driven Treasury workflows using:
  
• 
  Vertex AI
• Large Language Models (LLMs)
• Vector search / embeddings
  
• 
  Partner with analysts to productionize AI-assisted research, analysis, and reporting
• Evaluate and integrate emerging open-source AI and data tooling
  

DevOps & CI/CD

• Establish and enforce CI/CD pipelines for data and AI workloads
• Partner with security and platform teams to align with enterprise standards
• Promote Infrastructure-as-Code and automation-first practices
  

Technical Leadership

• Act as a technical thought leader within Treasury Technology
• Mentor engineers and analysts on modern data and AI practices
• Influence standards, patterns, and tooling choices across the organization
  

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



Requisition #: 2026-121170

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Requirements

2026-121170