Senior Software Engineer - Enterprise Architecture & AI Solutions Engineering
Your Opportunity
Your opportunity
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).
What you have
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science or equivalent professional experience.
- Demonstrated senior-level engineering depth through hands-on ownership of full-stack systems shipped end to end.
- Proven experience designing and delivering AI systems in production environments.
- Depth in at least two of the following: agentic systems, tool orchestration, MCP or related protocols, retrieval-augmented generation, embeddings, vector search, knowledge retrieval pipelines, prompt/context engineering, formal AI evaluation, testing, and guardrails.
- Strong command of enterprise design patterns, domain-driven design, distributed systems, service interfaces, and production-ready architecture.
- Ability to decompose complex problems, define precise technical specifications, direct AI-assisted development effectively, and critically evaluate model-generated output.
- Strong working knowledge of cloud platforms with the ability to reason about scalability, resilience, cost, security, and production operations for AI workloads.
- Hands-on database expertise across relational, NoSQL, vector, or graph databases, including data modeling, query tuning, indexing, query plans, and storage trade-off decisions.
- Experience reviewing code, pairing with engineers, improving development practices, and setting engineering standards through shipped reference implementations.
- Strong communication, problem-solving, and collaboration skills with the ability to partner across business, technology, architecture, and engineering audiences.
- Commitment to responsible AI practices, including security, privacy, evaluation, governance, and safety built into delivery.
- Experience working in private-sector, startup, or highly ambiguous environments where you owned problems across multiple technical layers.
- Experience mentoring and growing engineers at multiple levels through code review, pairing, technical coaching, and example-setting.
- Deep understanding of the software development lifecycle with examples of improving delivery practices, engineering standards, or team effectiveness.
- Experience building reusable engineering frameworks, internal developer platforms, AI enablement tools, or enterprise-scale technical platforms.
- Familiarity with coding agents, large language model APIs, orchestration frameworks, retrieval pipelines, model evaluation approaches, and AI governance patterns.
- Ability to adapt quickly as priorities, platforms, frameworks, and product needs shift.
- Curiosity and continuous learning mindset, with the ability to stay current as AI engineering practices evolve quickly.
What’s in it for you
At Schwab, you’re empowered to shape your future. We champion your growth through meaningful work, continuous learning, and a culture of trust and collaboration—so you can build the skills to make a lasting impact. Our Hybrid Work and Flexibility approach balances our ongoing commitment to workplace flexibility, serving our clients, and our strong belief in the value of being together in person on a regular basis.
We offer a competitive benefits package that takes care of the whole you – both today and in the future:
- 401(k) with company match and Employee stock purchase plan
- Paid time for vacation, volunteering, and 28-day sabbatical after every 5 years of service for eligible positions
- Paid parental leave and family building benefits
- Tuition reimbursement
- Health, dental, and vision insurance
What you are good at
What you have
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science or equivalent professional experience.
- Demonstrated senior-level engineering depth through hands-on ownership of full-stack systems shipped end to end.
- Proven experience designing and delivering AI systems in production environments.
- Depth in at least two of the following: agentic systems, tool orchestration, MCP or related protocols, retrieval-augmented generation, embeddings, vector search, knowledge retrieval pipelines, prompt/context engineering, formal AI evaluation, testing, and guardrails.
- Strong command of enterprise design patterns, domain-driven design, distributed systems, service interfaces, and production-ready architecture.
- Ability to decompose complex problems, define precise technical specifications, direct AI-assisted development effectively, and critically evaluate model-generated output.
- Strong working knowledge of cloud platforms with the ability to reason about scalability, resilience, cost, security, and production operations for AI workloads.
- Hands-on database expertise across relational, NoSQL, vector, or graph databases, including data modeling, query tuning, indexing, query plans, and storage trade-off decisions.
- Experience reviewing code, pairing with engineers, improving development practices, and setting engineering standards through shipped reference implementations.
- Strong communication, problem-solving, and collaboration skills with the ability to partner across business, technology, architecture, and engineering audiences.
- Commitment to responsible AI practices, including security, privacy, evaluation, governance, and safety built into delivery.
- Experience working in private-sector, startup, or highly ambiguous environments where you owned problems across multiple technical layers.
- Experience mentoring and growing engineers at multiple levels through code review, pairing, technical coaching, and example-setting.
- Deep understanding of the software development lifecycle with examples of improving delivery practices, engineering standards, or team effectiveness.
- Experience building reusable engineering frameworks, internal developer platforms, AI enablement tools, or enterprise-scale technical platforms.
- Familiarity with coding agents, large language model APIs, orchestration frameworks, retrieval pipelines, model evaluation approaches, and AI governance patterns.
- Ability to adapt quickly as priorities, platforms, frameworks, and product needs shift.
- Curiosity and continuous learning mindset, with the ability to stay current as AI engineering practices evolve quickly.
Why Schwab?
At Schwab, “Own Your Tomorrow” embodies everything we do! We are committed to helping our employees unleash their potential and achieve their dreams. Our employees get to play a central role in disrupting a multi-trillion-dollar industry, creating a better, more modern way to build and manage wealth. We’re a modern financial services firm that stands apart from the industry, where you can go as far as your ambition takes you.
Hear from employees: What’s it like to work at Schwab!
The benefits of working at Schwab : a package designed to empower your health, wealth, career and life. Schwab is committed to building a diverse and inclusive workplace where everyone feels valued.
As an equal employment opportunity employer, our policy is to provide equal employment opportunities to all employees and applicants without regard to any status that is protected by law. (Please click here to see policy.)
Schwab is also an affirmative action employer, focused on advancing women, minorities, veterans, and individuals with disabilities in the workplace. We believe diversity and inclusion are part of our success as a company and our purpose of serving every client with passion and integrity.