Software Engineer III

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. 

As a Software Engineer III at JPMorganChase within the Chase Auto Finance, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
• Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
• Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
• Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
• Contributes to software engineering communities of practice and events that explore new and emerging technologies
• Adds to team culture of diversity, opportunity, inclusion, and respect
• Develop and govern agentic coding pipelines leveraging LLMs, retrieval, and automated testing.
• Partner with Product, QA, SRE/Production Engineering, Security, and adjacent engineering teams to align on outcomes, communicate tradeoffs, and influence technical direction, while mentoring engineers, supporting hiring/technical evaluation, and driving continuous improvement in team practices.

Required qualifications, capabilities, and skills

• 10+ years of applied software engineering experience with formal training/certification (or equivalent), delivering solutions end-to-end across design, development, testing, deployment, and production operations.
• Strong Java engineering background building cloud-native, microservices-based applications using Spring Boot/Spring Cloud.
• Proven experience with event-driven architectures and data platforms: Kafka, SQL, RDBMS, and NoSQL databases (e.g., Cassandra).
• Expertise in CI/CD and automation using modern toolchains (e.g., Jenkins, Bitbucket, JIRA) and Agile delivery practices.
• Strong focus on operational excellence: observability/monitoring and incident readiness using Splunk, Dynatrace, and Datadog.
• Deep understanding of application resiliency, security, chaos engineering, and performance testing (e.g., BlazeMeter).
• Domain knowledge of auto financial services and the technology ecosystems supporting lending/servicing and related integrations.
• Ability to design and operate agent-based LLM workflows for software delivery (plan/write/test/iterate) with tool/function calling, guardrails, and human-in-the-loop controls.
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.

Preferred qualifications, capabilities, and skills

• Familiarity with modern front-end and back-end technologies
• Exposure to cloud technologies
• Exposure to AI tools