The Portfolio Performance Engineering team is looking for a talented technologist to be a Technical Lead for performance platform. The candidate will be a member of a small team of architects setting directions and leading teams and migrating platforms to the cloud. We build highly scalable, low-latency applications supporting and calculating performance for over 50 million Schwab's clients every single day. This is a unique position for somebody who loves technology. They get to be hands on and experiment, do Proof-Of-Concepts, mentor teams, provide architectural guidance and at the same time learn more about AI and other cutting-edge technologies and increase their own breadth of knowledge. This is an exciting opportunity to join a highly visible team that delivers innovative business solutions leveraging emerging technologies at Schwab. 

Position Responsibilities:

You will be joining us as a Technical Lead focused on providing architectural guidance across multiple projects and teams.  We are looking for a curious person with excellent technical skills, leadership and communication to guide the team through technology challenges while driving toward a target architecture. This position will report to a Director of Portfolio Management.

• • Collaborate with stakeholders to design scalable solutions and simplify complex problems into effective, maintainable approaches.

• • Lead end-to-end delivery of integrations, SSO, security, and customizations, including requirements gathering and technical design.

• • Provide expert guidance to teams, enforce design/coding standards, and ensure high-quality implementation and reusable components.

• • Drive knowledge sharing, promote reusable frameworks, and evaluate emerging technologies to solve evolving business challenges.

• • Lead the adoption and scaling of AI-assisted development practices across teams.
  • Coach engineers on effective AI usage and prompt engineering techniques.
  • Drive innovation and efficiency by embedding AI across the SDLC while establishing appropriate governance and best practices.

Required Qualifications:

• 8+ years of solid development experience in distributed and cloud platforms
• 5+ years of experience as an architect in building complex, highly scalable and low-latency applications
• Experience with C# and/or Java in a Windows/Linux data center environment
• Experience owning and operating multiple instances of a mission critical service
• Experience with Agile development methodology and Test Driven Development (TDD)
• Experience with cloud services including Infrastructure as a Service (IaaS), Pivotal Cloud Foundry, and public cloud providers
• Experience using metrics to drive operational excellence
• Experience growing high performing engineering teams
• Good judgment and the ability to handle stressful situations
• Broad knowledge of software engineering: languages, frameworks, techniques, industry trends, etc.
• Experience as a technical leader in an organization.  This includes coaching and mentoring, working through complex problems, and working with our business partners to deliver an amazing experience for our clients.  You have qualities that engineers recognize and respect.
• The ability to step in and code to drive a solution that your engineers can build upon
• Deep knowledge of REST and the Web Services
• Knowledge and experience with server-side .NET development
• Knowledge of NoSQL and SQL databases (Aerospike, MongoDB, Oracle are preferred)
• Knowledge of messaging systems like RabbitMQ and Kafka 

AI Enablement & Developer Productivity:

• Demonstrated experience using GitHub Copilot and other AI-assisted development tools to accelerate coding, improve code quality, and streamline delivery workflows.
• Champion the adoption of AI-driven development practices across engineering teams, driving measurable improvements in productivity and efficiency.
• Educate and mentor teams on effective and responsible use of AI tools, including prompt engineering, code validation, and security considerations.
• Identify and implement practical use cases for AI across the software development lifecycle (e.g., code generation, testing, documentation, and troubleshooting).
• Establish best practices and governance for AI-assisted development to ensure accuracy, maintainability, and compliance with enterprise standards.
• Continuously evaluate emerging AI technologies and integrate them into engineering workflows to enable faster execution and innovation at scale.

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