Lead Software Engineer - AI & Platform Modernization

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.

Join us as we lead the most significant technical transformation in retirement services—architecting AI-native systems using Retrieval-Augmented Generation (RAG) and Model Context Protocol (MCP) to modernize legacy applications through Domain-Driven Design. You’ll work at the intersection of cutting-edge AI technology and complex financial domains, building intelligent systems that directly impact millions of people’s retirement security. With executive-level support, substantial budget, and technical freedom, you’ll pioneer RAG architecture and multi-agent orchestration in a highly regulated, mission-critical environment.

This is your chance to establish yourself as an industry-leading expert in AI-driven legacy transformation, defining patterns that will become case studies for years to come. We thrive together as One Schwab, guided by respect and care for all. Our inclusive, collaborative, and positive environment values and supports every team member, empowering you to make a real impact.

What you have

To fulfill our promise of “challenging the status quo,” this role has specific qualifications that successful candidates should have.

Required Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, or related technical field, or equivalent practical experience
• 7+ years of professional software engineering experience
• 3+ years in technical leadership or architect role
• 3+ years of hands-on experience building and deploying solutions in public cloud environments (GCP, AWS, Azure).
• 2+ years hands-on experience with AI/ML implementation and production deployment
• Experience with legacy application modernization and migration projects
• Hands-on experience with Large Language Models (e.g., GPT-5, Claude, Gemini, PaLM)
• Production implementation of RAG architectures
• Experience with Model Context Protocol (MCP) or AI agent orchestration frameworks
• Experience with vector databases (Pinecone, Weaviate, Chroma, or Vertex AI Vector Search)
• Prompt engineering and LLM optimization techniques
• Experience with Vertex AI platform on Google Cloud Platform or Bedrock platform on AWS
• Proficiency in Python (AI/ML development), .NET (enterprise services), and SQL (database design)
• Experience with event streaming platforms (Kafka, Pub/Sub, or similar)
• Proven ability to lead technical teams and mentor engineers
• Excellent communication skills—proven ability to explain complex technical concepts to non-technical stakeholders
• Experience collaborating with product managers, data scientists, and business stakeholders
• Problem-solving mindset with a focus on business outcomes

Preferred Qualifications

• Master’s degree in Computer Science, AI/ML, or related field
• 10+ years of professional software engineering experience
• 2+ years’ experience implementing RAG architectures using frameworks like LangChain, LlamaIndex, or Haystack
• Financial services or highly regulated industry experience
• Experience in retirement services, wealth management, or FinTech
• ML Ops and model lifecycle management
• Multi-cloud experience (AWS/Azure in addition to GCP)
• Advanced GKE and service mesh
• Cloud Build and advanced CI/CD pipelines
• IAM and Secret Manager best practices
• JavaScript/TypeScript for full-stack context
• Familiarity with Delphi, .NET, C#
• Event Sourcing and CQRS patterns
• Database design and optimization (relational and NoSQL)
• Saga patterns for distributed transactions
• Service mesh and API Gateway patterns
• A/B testing frameworks and experimentation platforms
• Experience working in Agile/Scrum environments at scale
• Track record of driving consensus in cross-functional teams
• Public speaking or technical writing experience (blogs, conferences, patents)
• Contributions to open-source AI/ML projects
• Knowledge of retirement services (401k, IRA, RMDs, rollovers)
• Familiarity with fiduciary responsibilities in financial technology
• Experience building systems with audit trails and explainability requirements
• Understanding of tax implications in retirement planning
• Google Cloud Professional Machine Learning Engineer, Cloud Architect, AWS/Azure Solutions Architect certifications