Director, Software Development & Engineering Senior (PL) - Broker Dealer Services Engineering

Your opportunity

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).

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 are seeking a seasoned and strategic Director to lead enterprise-wide Broker-Dealer platform transformation across multiple domains, driving end-to-end re-platforming of core capabilities and shared services.

This high-impact role requires a blend of broker-dealer domain expertise, technical acumen, and change management leadership. The ideal candidate will re-engineer legacy systems, implement modernized broker-dealer capabilities, and ensure compliance with SEC/FINRA regulations. This role is accountable for cross-domain transformation outcomes and platform evolution, not individual domain delivery ownership. It carries explicit accountability for retiring legacy mainframe and tightly coupled systems and reducing overall platform complexity and risk.

As a member of the Broker Dealer Services Engineering leadership team, this role will define and operationalize an AI-first engineering model, embedding generative and agentic AI across the full software lifecycle to measurably transform how platforms are built, modernized, supported, and operated across our strategic broker dealer platform. This role requires an individual adept at navigating regulatory and organizational challenges inherent in a large financial institution, while promoting innovation, operational stability, resiliency, and efficiency.

We seek a transformation leader who combines strategic clarity, execution discipline, and the ability to drive change at scale. A proven track record of establishing AI-first teams and consistently delivering high-quality technology products and services in fast-paced, growth-focused settings is crucial for success in this position.

Key Responsibilities

• AI‑Driven Engineering Transformation: Lead the transformation of an established engineering organization from legacy, manual development practices to a GenAI‑first, agentic SDLC. Treat AI as a core production capability, not a side experiment—used across design, development, testing, modernization, documentation, and operations.
• Technology & Architecture leadership: Develop, lead, and execute a multi-year, enterprise-wide transformation strategy spanning multiple broker-dealer domains, aligning architecture, data, and platforms into unified target state architecture.
• Transformation Execution: Migrate legacy broker-dealer systems to modern architecture while executing structured legacy decommissioning plans, including system retirement, data migration, and cost/complexity reduction.
• Legacy Retirement Ownership: Define and execute a clear strategy for decommissioning legacy systems, including reverse engineering, domain decomposition, data migration, and measurable reduction of technical debt and operational risk
• Production Support & Operational Resiliency: Own production support outcomes for critical broker-dealer platforms, ensuring high availability, incident readiness, rapid issue resolution, effective root-cause analysis, and continuous improvement across monitoring, alerting, runbooks, release readiness, and operational controls.
• Stakeholder Management: Liaise with senior leadership and functional heads to align system capabilities with business goals, managing expectations and priorities across the organization.
• Vendor Strategy & Management: Evaluate, select, and manage relationships with key IT services vendors and third-party product vendors.
• Team Leadership: Lead cross-functional teams of IT professionals across multiple countries, fostering a high-performance culture aligned with the new technical operating model. 
• Execution Focus: Demonstrated ability to operationalize strategy and deliver complex, multi-year programs on time and within budget.
• Talent Management: Passionate and proven ability to identify, mentor, and develop technical and managerial talent at scale.
• Communication: Outstanding executive-level written and verbal communication skills.

What you have

Required Qualifications

• Education: Bachelor’s degree in computer science, Information Systems, or a related field. 
• Experience: 10+ years in managing broker-dealer systems with a focus on system transformation.
• Domain Expertise: Deep understanding of broker-dealer capabilities and operations.
• Transformation Leadership: Proven track record of leading large-scale, complex technology projects from conception to implementation.
• Technical Acumen: Broad and deep knowledge of IT/software technologies and trends, domain knowledge and experience in infrastructure support, application development, and cloud-based application development, web services, middleware, operating systems, databases, networking, and security. Own AI-first delivery across the SDLC, including use of generative and agentic AI for legacy system understanding, requirements analysis, automated testing, code modernization, and production operations—with clear, measurable improvements in velocity, quality, and cost.
• Production Operations:Demonstrated experience leading production support for business-critical financial services platforms, including incident management, problem management, service restoration, operational risk reduction, resiliency practices, and partnership with business, operations, risk, compliance, and infrastructure teams.
• Leadership Skills:Proven ability to build and lead high-performing, globally distributed teams in a fast-paced environment. Proven experience transforming teams from legacy, mainframe-centric ways of working to modern, distributed engineering practices by leading large-scale adoption of generative and agentic AI as a primary transformation lever, not an augmentation—redefining engineering productivity, system design, and delivery practices. Experience with owning end-to-end legacy exit strategies, including reverse-engineering COBOL/mainframe systems and successfully decommissioning them through modern distributed platform implementations using agentic AI.
• Stakeholder Management: Proven track record of managing stakeholders through influence and setting appropriate expectations and holding them accountable to ensure faster delivery to market.