Java/AI Software Developer

Charles Schwab Inc.•Austin, TX

5d•$126,000 - $140,000•Onsite

About The Position

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 Sr. Specialist – Software Development and Engineering, you will play a critical role in designing, developing, and evolving scalable technology solutions that support high-volume, highly available environments. In close partnership with both technical and business stakeholders, you will translate complex requirements into effective architecture and applications, contributing to strategic initiatives that modernize systems and improve performance across platforms. This role emphasizes driving outcomes through thoughtful problem-solving, including identifying gaps in processes, optimizing programming environments, and influencing solution design aligned with organizational priorities. You will help shape end-to-end development efforts—from researching and validating new technologies to building proof of concepts and implementing production-ready solutions. Your work will support continuous improvement across development lifecycles, including enabling automated testing, enhancing deployment pipelines, and strengthening system reliability. Through collaboration, you will engage cross-functional partners, bridge technical and non-technical perspectives, and contribute to planning discussions that guide long-term technology direction. Additionally, you will support knowledge sharing and mentorship, helping elevate team capabilities while fostering adaptability in a rapidly evolving environment. Demonstrated exposure to, or hands-on experience with, GenAI coding assistants used across day-to-day engineering workflows in the SDLC—implementation, refactoring, unit testing, regression support, code reviews, scripting/automation, troubleshooting, and documentation—while applying engineering judgment and validation. Practical familiarity with tools such as GitHub Copilot or Claude Code is expected.

Requirements

Demonstrated exposure to, or hands-on experience with, GenAI coding assistants used across day-to-day engineering workflows in the SDLC—implementation, refactoring, unit testing, regression support, code reviews, scripting/automation, troubleshooting, and documentation—while applying engineering judgment and validation.
Practical familiarity with tools such as GitHub Copilot or Claude Code is expected.
Uses AI assistance for common dev tasks (code suggestions, test generation, review support, automation scripts, troubleshooting) with clear ownership for correctness and quality.
Applies GenAI in ways that reduce context switching and accelerate delivery across typical workflows (not limited to writing new code).
Demonstrates practical familiarity with GitHub Copilot and/or Claude Code within IDE/CLI-style workflows.
Working knowledge of agentic workflows, spec-driven development (translating low-level design artifacts such as class structures, API contracts, and data models into structured specs that guide AI-assisted implementation), and custom instructions and prompt engineering, with the ability to establish team-level practices for effective AI-assisted development.
3+ years of experience with Java, Spring framework, cloud development, and web services (REST, SOAP) supporting high-volume, highly available applications
2+ years of experience working with ETL processes, data pipelines, or messaging frameworks
1+ years of experience of any Spring batch and messaging pub/sub applications using Java frameworks
1+ years of experience with CI/CD tools such as Bamboo, Bitbucket/Git, or similar
1+ years of experience with cloud platforms such as AWS, GCP, or Pivotal Cloud Foundry (PCF)
1+ years of experience with distributed databases such as PostgreSQL, Aerospike, or Yugabyte
1+ years of experience supporting IT transformation or system modernization initiatives (e.g., legacy mainframe to distributed platforms)
1+ years of experience using AI assistance for common dev tasks (code suggestions, test generation, review support, automation scripts, troubleshooting) with clear ownership for correctness and quality.

Nice To Haves

Experience working in Agile environments and applying Agile methodologies
Familiarity with Atlassian tools such as JIRA
Experience with .NET technologies, including C# and Visual Studio
Experience with messaging technologies such as RabbitMQ
Background in financial services or regulated industries
Experience with Test-Driven Development (TDD) practices
Strong problem-solving and analytical skills with the ability to make sound decisions in complex scenarios
Demonstrated ability to collaborate effectively across diverse teams, including offshore partners
Strong communication skills with the ability to translate technical concepts for non-technical stakeholders
Ability to document architecture, design, and technical specifications clearly and effectively
Proficiency in creating architectural diagrams and technical documentation
Willingness to learn and adapt to new technologies, tools, and processes

Responsibilities

Designing, developing, and evolving scalable technology solutions that support high-volume, highly available environments.
Translating complex requirements into effective architecture and applications.
Contributing to strategic initiatives that modernize systems and improve performance across platforms.
Identifying gaps in processes, optimizing programming environments, and influencing solution design aligned with organizational priorities.
Shaping end-to-end development efforts—from researching and validating new technologies to building proof of concepts and implementing production-ready solutions.
Supporting continuous improvement across development lifecycles, including enabling automated testing, enhancing deployment pipelines, and strengthening system reliability.
Engaging cross-functional partners, bridging technical and non-technical perspectives, and contributing to planning discussions that guide long-term technology direction.
Supporting knowledge sharing and mentorship, helping elevate team capabilities while fostering adaptability in a rapidly evolving environment.
Using AI assistance for common dev tasks (code suggestions, test generation, review support, automation scripts, troubleshooting) with clear ownership for correctness and quality.
Applying GenAI in ways that reduce context switching and accelerate delivery across typical workflows (not limited to writing new code).
Establishing team-level practices for effective AI-assisted development.