Software Engineer III

JPMorgan Chase · ✓ Verified company
📍 Hyderabad, Telangana, India · On-site · Full-time

About the role

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