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About the Role

In this hands-on senior engineering role, you’ll help build and evolve the internal platforms, reusable frameworks, AI tooling, golden paths, agentic infrastructure, and governance guardrails that enable Schwab engineering teams to scale AI responsibly and effectively. You’ll contribute directly to platforms including technical debt management, enterprise governance, agent registries, agent pipelines, architecture assessment, and internal AI enablement solutions, using strong engineering judgment to design systems that are scalable, secure, observable, and production-ready. This role is ideal for an architect or senior engineer who enjoys working cross-functionally across technologies, applying AI and large language models as force multipliers, and moving between platforms, frameworks, and product priorities as enterprise needs evolve. Your impact will come through the systems you design and ship, the standards you model, and the way you partner with architects, engineers, and stakeholders to solve complex problems with clarity, precision, and accountability.

Responsibilities

Build and evolve internal platforms, reusable frameworks, AI tooling, golden paths, agentic infrastructure, and governance guardrails.
Contribute directly to platforms including technical debt management, enterprise governance, agent registries, agent pipelines, architecture assessment, and internal AI enablement solutions.
Design systems that are scalable, secure, observable, and production-ready.
Partner with architects, engineers, and stakeholders to solve complex problems.
Ship systems and set standards through shipped reference implementations.
Review code and pair with engineers.
Improve development practices and set engineering standards.
Mentor and grow engineers through code review, pairing, technical coaching, and example-setting.
Build reusable engineering frameworks, internal developer platforms, AI enablement tools, or enterprise-scale technical platforms.

Requirements

Bachelor’s or Master’s degree in Computer Science or equivalent professional experience.
8+ years of software engineering experience, with demonstrated expertise designing and delivering complex, scalable software solutions and driving technical outcomes across the development lifecycle.
3+ years demonstrating senior-level engineering depth through hands-on design and ownership of full-stack systems shipped end to end.
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.
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 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.
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.
Deep understanding of the software development lifecycle with examples of improving delivery practices, engineering standards, or team effectiveness.
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.

Skills

Enterprise design patterns
Domain-driven design
Distributed systems
Service interfaces
Production-ready architecture
AI-assisted development
Agentic systems
Tool orchestration
MCP or related protocols
Retrieval-augmented generation
Embeddings
Vector search
Knowledge retrieval pipelines
Prompt/context engineering
Formal AI evaluation
AI testing
AI guardrails
Cloud platforms
Scalability
Resilience
Cost optimization
Security
Production operations for AI workloads
Relational databases
NoSQL databases
Vector databases
Graph databases
Data modeling
Query tuning
Indexing
Query plans
Storage trade-off decisions
Coding agents
Large language model APIs
Orchestration frameworks
AI governance patterns
Communication
Problem-solving
Collaboration

Location

On site

Work Type

Full-time
On site

Experience Level

Senior
8+ years of software engineering experience
3+ years demonstrating senior-level engineering depth

Education Level

Bachelor’s degree in Computer Science
Master’s degree in Computer Science
Equivalent professional experience

Salary/Compensations

Eligible for bonus or incentive opportunities

About the Company

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.

Equal Opportunity

Applicants must be currently authorized to work in the United States on a full-time basis without employer sponsorship.