Software Engineer III

JPMorgan Chase JPMorgan Chase · Banking · Hyderabad, Telangana, India · Consumer & Community Banking

Software Engineer III at JPMorgan Chase, focused on building and governing agentic coding pipelines using LLMs, retrieval, and automated testing. The role involves designing and operating LLM workflows for software delivery, including tool/function calling and guardrails, and utilizing AI-assisted development tools while critically evaluating their outputs. Experience with Java, cloud-native applications, event-driven architectures, and CI/CD is required, along with a strong focus on operational excellence and domain knowledge in auto financial services.

What you'd actually do

  1. 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
  2. Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
  3. Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
  4. Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
  5. Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture

Skills

Required

  • 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.

Nice to have

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

What the JD emphasized

  • Develop and govern agentic coding pipelines leveraging LLMs, retrieval, and automated testing.
  • 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.

Other signals

  • Develop and govern agentic coding pipelines leveraging LLMs, retrieval, and automated testing.
  • 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.