Lead AI Solutions Engineer, AI.x

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, this organization has a preferred candidate identified for this role.

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 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).

As a Lead AI Solutions Engineer within Enterprise AI, you will shape how secure, scalable AI solutions move from business opportunity to production. You will own the technical direction and delivery of a portfolio of concurrent initiatives, establishing reusable architectures, engineering standards, testing practices, and quality controls that accelerate responsible innovation across the firm.

Working across engineering, architecture, cybersecurity, data, risk, compliance, and legal teams, you will translate complex requirements into practical solutions and make sound decisions when priorities, capacity, and risk must be balanced. You will provide technical leadership without direct authority, mentor contributors, and communicate clear, evidence-based recommendations to senior leaders. Your systems thinking, problem-solving, and engineering judgment will help determine which AI capabilities Schwab advances and how those solutions are operated responsibly at enterprise scale.

What you have

Required Qualifications

• 12+ years of experience in software engineering, systems engineering, solution architecture, or applied AI development, including sustained technical leadership of enterprise-scale solutions
• Experience owning concurrent technical deliveries from design through production, stabilization, ongoing support, and retirement
• Demonstrated success delivering production AI or large language model solutions that remain supported and in use after launch
• Technical expertise across APIs, identity, enterprise data platforms, access controls, system integration, and software development lifecycle practices
• Experience establishing architecture patterns, engineering standards, testing methods, evaluation practices, and production quality controls
• Ability to apply problem solving, decision making, and risk management in a regulated environment
• Proven ability to lead and mentor technical contributors without formal authority
• Strong communication skills, including presenting defensible technical recommendations to senior leadership, governance, risk, and engineering audiences 

Preferred Qualifications

• Financial services or comparable highly regulated industry experience
• Experience with Generative AI, agent frameworks, orchestration, retrieval patterns, model evaluation, and prompt engineering
• Experience with Microsoft Azure, Microsoft Copilot, Copilot Studio, or comparable enterprise AI platforms
• Experience contributing to AI governance, model risk, regulatory compliance, or control frameworks
• Background connecting engineering strategy, business needs, platform investment, and measurable value 

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