Careers at Charles Schwab

Your opportunity

At Charles Schwab, our purpose is simple: we champion client’s goals with passion and integrity. Guided by honesty, mutual respect and a commitment to doing what’s right, we bring innovation, education, and service together to help shape financial futures. Our people are the foundation of our success – they approach their work with curiosity and collaboration, coming together to create solutions that make a meaningful impact for clients and communities. As we expand into India, we are bringing this same culture of inclusion, learning, and opportunity to new talent. Joining us means becoming part of a global team where your work matters and your future can take shape

At Charles Schwab, our purpose is simple: we champion client’s goals with passion and integrity. Guided by honesty, mutual respect and a commitment to doing what’s right, we bring innovation, education, and service together to help shape financial futures. Our people are the foundation of our success – they approach their work with curiosity and collaboration, coming together to create solutions that make a meaningful impact for clients and communities. As we expand into India, we are bringing this same culture of inclusion, learning, and opportunity to new talent. Joining us means becoming part of a global team where your work matters and your future can take shape

What you have

Key Responsibilities

​​The Schwab Asset Management (SAM) Technology organization is a part of Schwab Technology Services that is responsible for Schwab's investment management, operations, data, and research platforms. Everything that SAM Tech builds serves Schwab’s mission of helping clients reach their financial goals.

As a Sr. Manager, Software Development and Engineering - Research Technology in the SAM Investment Research Technology group, you will lead of team of engineering professionals focused on delivering cutting-edge research, data, distribution, and AI enablement capabilities designed to advance SAM business opportunities and to support the Schwab Center for Financial Research (SCFR) in its mission to provide clients and advisors actionable investment advice. We curate datasets for both exploratory and product-focused research, we implement and maintain investment models, we maintain asset allocation schema and asset classification workflows, and we systematically deliver these datasets to downstream clients and AI applications throughout the enterprise.  This role will be responsible for the ongoing operation and modernization of our research and distribution platforms and for delivering new models, data, and other capabilities into production. The Investment Research Technology Group operates within a mature Agile and DevOps model in partnership with our business stakeholders, requiring active engagement with Product Owners, Researchers, Architects, and other partners — in managing requirements, design, coding, testing (unit and functional), deployment, and post-release support.​

​​▪ Lead a team of engineering professionals responsible for creating and delivering data platforms, models, and other quantitative research capabilities used by SAM/SCFR researchers to develop cutting-edge investment products
▪ Leverage your knowledge of the investment management domain to interface with business partners in SAM and SCFR and associated Schwab enterprises to gather, refine, and interpret business and technical requirements
▪ Represent SAM Investment Research Tech in cross-functional forums to negotiate program priorities, resourcing, and trade-offs
▪ Provide technical leadership in designing and implementing modern data platforms spanning multiple asset classes and serving the needs of diverse research teams
▪ Oversee delivery and ongoing enhancements to full-stack applications utilized by business users to oversee data production activities and provide data validation for large datasets
▪ Implement and support model operations processes and controls to enable efficient and reproducible research and provide post-release model monitoring
▪Build data visualizations and other tooling to enable model researchers to efficiently monitor model performance and stability, as well as to interpret model outputs.
▪ Assist in selection and integration of data related tools, frameworks, and applications required to expand platform capabilities
▪ Lead proof-of-concepts to understand the appropriateness of new methodologies and/or technologies for our platforms
▪ Build high-performing, collaborative development teams that deliver predictably within the Agile framework as well as operate effectively within the broader Schwab technology organization
▪ Develop and motivate individual engineering staff to deliver high-quality solutions that meet the needs of clients and business partners
▪ Support staff in career development to unlock long-term value for the organization.
▪ Promote and sustain a culture of engineering excellence with a focus on quality and transparency
▪ Operate successfully within the Schwab technology ecosystem, partnering with architects, engineers, business analysts, scrum masters, and other infrastructure, security, and governance teams to deliver products in compliance with enterprise standards
▪ Be a champion of new ways of collaborating with technology and business partners
▪ Influence and implement improvements and efficiencies in both the technical and non-technical aspects of the development process​

Required Qualification

​​▪ Degree in computer science, information systems, math, engineering, or other technical field, or equivalent experience
▪ Six or more years of software engineering experience focused on data-intensive systems leveraging Python, Java and/or similar languages (e.g. R, Matlab, Julia)
▪ Experience building and leading technical teams delivering high-quality software in a regulated operating environment
▪ Experience growing mature, high-performing engineering teams, including talent management, coaching, and career development
▪ Strong communication skills and ability to drive alignment and consensus both within and across teams/organizations
▪ Experience collaborating with investment teams to support research workflows, data analysis, model development, and data distribution activities
▪ Proven ability designing, developing, and operating data-intensive systems processing large financial datasets, with a strong focus on performance, reliability, and timely data delivery
▪ Proficiency in designing and implementing data models to support efficient data storage, integration, and retrieval of financial datasets
▪ Foundational understanding of modern AI architectures, including Model Context Protocol (MCP) and Retrieval-Augmented Generation (RAG).
▪ Understanding of data quality frameworks and controls, including monitoring, validation, lineage tracking, and governance processes to ensure data accuracy, completeness, and reliability
▪ Experience leveraging continuous integration/development tools (e.g. Jenkins, Docker, Containers, OpenShift, Kubernetes, and container automation) in a CI/CD pipeline
▪ Proficiency building integration and regression testing frameworks to ensure system stability and performance
▪ Proven ability to partner with researchers, product leaders, and technology stakeholders to negotiate priorities and deliver business value
▪ Experience managing complex technology portfolios, balancing innovation, operational reliability, and regulatory constraints
▪ Demonstrated capability to lead and motivate technical teams by building trust and emphasizing transparency in decision-making

Preffered Qualification

​​▪ Advanced degree in computer science, engineering, mathematics, quantitative finance, or a related technical discipline
▪ Demonstrated ability to influence technical and business strategy through deep domain expertise, data-driven decision making, and cross-functional leadership.
▪ Experience leading platform modernization, cloud adoption, or large-scale technology transformation initiatives within a regulated financial services environment.
▪ Hands-on experience with modern data lake platforms and architectures supporting investment management use cases, including the ingestion, storage, governance, and consumption of structured and unstructured datasets; Snowflake experience a plus
▪ Experience designing and implementing distributed compute architectures to enable scalable, high-throughput data workflows and analytics
▪ Experience delivering capabilities for AI enablement, such as MCP Servers, RAG indexes, etc.
▪ Track record of identifying and implementing innovative technologies, engineering practices, or process improvements that increase team effectiveness
▪ Experience communicating complex technical concepts to diverse audiences, including senior business and technology leaders
▪ Proven ability to build organizational capability through mentoring, knowledge sharing, and the development of technical talent across teams
▪ Experience synthesizing input from multiple stakeholders to balance competing priorities, drive alignment, and create achievable implementation plans
▪ Familiarity with quantitative investment research methodologies, including factor modeling, portfolio construction, risk analytics, performance attribution, or backtesting​​