Director, Software Development & Engineering Senior (PL)

Your Opportunity

Schwab remains committed to providing increased visibility to career growth opportunities and job requirements. This posting announcement is part of increased transparency and while all qualified applicants will be reviewed and considered, a preferred candidate has been identified for this role.   

We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in Southlake, TX.

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 hands-on, strategic Director to lead AI Solutions, and Standards across Cross Enterprise Services (CES). This is not a traditional application development Director People Leader role tied to a single platform or domain. Instead, you will lead a dedicated team that builds reusable AI capabilities, sets agentic engineering standards, and accelerates AI adoption across every CES domain. As CES has earned recognition across Schwab Technology Services (STS) for driving measurable outcomes from AI, this role exists to turn that momentum into consistent, governed, enterprise-grade practice.

As the AI technical leader for CES, you will lead a small team of engineers who POC and drive implementation of AI solutions directly across CES domains. You will partner closely with your CES leadership peers, the AI Champions network, and the broader AI Enablement Engineering (AIEE) effort to move proven local innovations into shared standards and scalable. Success requires a builder-leader who is deeply technical, fluent in agentic AI, business-savvy, and able to bring stakeholders along through change.

Why this role / Why now

CES is transitioning from broad AI experimentation to a standardized, enterprise-scale operating model. The organization is running AI-DLC pods, contributing hundreds of assets to the shared DevAI ecosystem, and modernizing legacy systems with agentic approaches, but teams are building agents inconsistently and without common standards. This role owns the mandate to fix that: to help define how agents are built, to accelerate AI-DLC adoption, and to identify AI solutions that every CES domain can reuse. You will have influence on the standards, architecture, and ways of working that shape AI engineering across CES and STS.

Key Responsibilities

• Agentic Consistency & Standards: Define and drive enterprise standards for how agents are built across CES and STS. Own the agent specification including required components, context and memory management, auditability, accuracy thresholds, and governance, so agents are constructed consistently, reliably, and securely, with reduced token consumption and measurable output quality.
• AI Enablement & Technical Leadership: Serve as the AI technical lead for CES. Lead a dedicated team of engineers who POC and implement AI solutions across CES domains. Partner with CES leadership peers and define a clear role within the AI Champions program to align enablement, adoption, and hands-on delivery.
• Accelerate AI-DLC in CES: Establish clear entry criteria, standards, and a repeatable operating model for AI-Driven Development Lifecycle (AI-DLC) teams. Help domains move from experimentation to sustained, measurable adoption using agent-driven planning, development, testing, and delivery.
• AI Solutions Delivery: Identify, POC, and propose AI solutions, agents, and frameworks that address CES-wide pain points and can be adopted across domains, reducing duplication and improving consistency.
• Legacy Modernization with AI: Lead AI-specific modernization efforts across CES, including COBOL and mainframe reverse engineering into functional specifications and forward engineering into modern, distributed architectures.
• Forward Deployed Engineering (FDE) Capability: Help define and develop the Forward Deployed Engineer capability within CES, engineers who combine business understanding, technical depth, advanced AI skills, and strong collaboration to design optimized, outcome-focused solutions that reduce human touchpoints and improve the client experience. Build this capability internally through coaching and upskilling.
• Governance, Quality & Resilience: Establish governance, quality controls, auditability, and operational resilience for AI-assisted and agentic workflows as CES becomes increasingly dependent on them.
• Measurement & Outcomes: Define leading and lagging measures of AI effectiveness, adoption, maturity, and capacity unlock, tying AI investments to measurable productivity and business outcomes.
• Team Leadership: Attract, develop, and lead a high-performing engineering team; foster a culture of innovation, accountability, and continuous improvement across a geographically distributed (onshore and offshore) footprint.
• Stakeholder Management & Communication: Influence and align peers, domain leaders, and senior leadership; translate technical direction into outcomes and bring stakeholders along through change.

What you have

Required Qualifications

• Education: Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.
• Experience: 10+ years of software engineering and application development experience, including progressive people leadership responsibility as a leader of leaders or senior engineering teams.
• Agentic & GenAI Expertise: Deep, hands-on expertise with GenAI and agentic AI, including designing, building, and governing agents (context and memory management, prompt and spec-driven development, MCP, evaluation of output quality, and token efficiency).
• Standards: Proven ability to define engineering standards, and reusable frameworks, that scale across multiple teams rather than a single application or domain.
• AI-Native Delivery: Demonstrated success embedding AI across the full software development lifecycle and moving teams beyond pilots to sustained, measurable adoption.
• Modernization Experience: Experience using AI to reverse-engineer legacy/COBOL or mainframe-centric systems and forward-engineer them into modern, distributed platforms.
• Technical Acumen: Broad and deep knowledge of software architecture, distributed systems, cloud-based development, CI/CD, security, and modern engineering practices.
• Leadership Skills: Experience building and developing high-performing engineering teams in a fast-paced environment, including geographically distributed and offshore teams.
• Stakeholder Management & Executive Presence: Proven ability to influence peers and senior leaders, set expectations, and drive accountability toward faster delivery.

Preferred Qualifications

• Financial services experience, preferably within brokerage, trading, or securities processing environments.