Senior Software Engineer - Enterprise Architecture & AI Solutions Engineering
Charles Schwab7 days ago
Responsibilities
- Build and evolve internal platforms, reusable frameworks, AI tooling, golden paths, agentic infrastructure, and governance guardrails.
- Deliver production-ready AI systems, agent registries, agent pipelines, technical debt management platforms, and architecture assessment solutions.
- Design scalable, secure, observable distributed systems and enterprise architecture using strong engineering judgment.
- Apply agentic systems, tool orchestration, retrieval-augmented generation, embeddings, vector search, prompt/context engineering, evaluation, testing, and guardrails.
- Make cloud, database, data modeling, query tuning, indexing, query-plan, and storage trade-off decisions for AI workloads.
- Review code, pair with engineers, mentor team members, and establish engineering standards through reference implementations.
- Partner with architects, engineers, business stakeholders, and technology leaders to solve complex enterprise problems.
- Embed responsible AI practices covering security, privacy, evaluation, governance, and safety into delivery.
Requirements
- Bachelor’s or Master’s degree in Computer Science, or equivalent professional experience.
- Senior-level hands-on ownership of full-stack systems delivered end to end.
- Proven experience designing and delivering AI systems in production environments.
- Depth in at least two areas including 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 knowledge of enterprise design patterns, domain-driven design, distributed systems, service interfaces, and production-ready architecture.
- Ability to define precise technical specifications, direct AI-assisted development, and critically evaluate model-generated output.
- Strong working knowledge of cloud platforms and production operations for AI workloads, including scalability, resilience, cost, and security considerations.
- Hands-on experience with relational, NoSQL, vector, or graph databases, including data modeling, query tuning, indexing, query plans, and storage trade-offs.
- Experience reviewing code, pairing with engineers, improving development practices, and setting engineering standards.
- Preferred: experience in private-sector, startup, or ambiguous environments with ownership across multiple technical layers.
- Preferred: experience mentoring and developing engineers at multiple levels.
- Preferred: experience building reusable engineering frameworks, internal developer platforms, AI enablement tools, or enterprise-scale technical platforms.
- Preferred: familiarity with coding agents, large language model APIs, orchestration frameworks, retrieval pipelines, model evaluation approaches, and AI governance patterns.
Benefits
- Fully on-site work in the specified location(s), reflecting Schwab’s emphasis on in-office collaboration.
- Eligibility for bonus or incentive opportunities in addition to the salary range.
Categories
About Charles Schwab
Charles Schwab is a different kind of investment services firm – one that strives to disrupt the status quo of the traditional Wall Street approach on behalf of our clients. We believe today, as we did on Day 1, that when you find ways to improve the investing experience for your clients, then business results will follow. Follow our company culture at #SchwabLife and see how we give back at #Schwab4Good. Support hours: 7 a.m.–7 p.m. CT or 24/7 at schwab.com/contact-us. Social Media Disclosures: https://www.aboutschwab.com/social-media (#0424-TM8W)