Software Engineer III

JPMorganChase | Asset and Wealth Management | Infrastructure Team

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 Asset and Wealth Management Infrastructure team, 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.

• Executes software solutions, design, development, and technical troubleshooting with creative problem-solving to optimize system reliability, scalability, and performance.
• Creates secure and high-quality production code and maintains services/algorithms that integrate reliably with dependent systems and platforms.
• 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 CI/CD and enterprise-authorized AI-assisted development/automation) to reduce manual intervention and increase operational efficiency across deployment, monitoring, and operations.
• Produces architecture and design artifacts for complex applications including infrastructure, configuration, and network as code; accountable for ensuring design constraints and non-functional requirements are met in implementation.
• Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets to drive continuous improvement of software applications and system operations.
• Proactively identifies hidden problems and patterns in production issues and data and uses these insights to improve coding hygiene, system architecture, and operational stability.
• Follows best practices in SRE, DevOps, and observability to monitor platform health, proactively address risks, and troubleshoot complex production incidents.
• Analyzes large volumes of structured, unstructured, and telemetry data to uncover trends/anomalies and translate findings into actionable reliability and performance improvements.

• Formal training or certification on software engineering concepts and 3+ years of applied experience.
• Experience in SRE/DevOps/Platform Engineering environments with demonstrated ownership of reliability, performance, and incident response.
• Experience with AWS services such as ECS, VPC, S3, IAM, Lambda, Aurora Postgres, Route53, ELB, API Gateway (and related cloud-native patterns).
• Strong understanding of automation and Infrastructure as Code (e.g., Terraform), including configuration and network as code for applications/platforms.
• Experience leading teams in the safe use of enterprise-authorized AI capabilities within the work environment for reliability engineering workflows, including validation habits and awareness of data sensitivity.
• Hands-on experience using enterprise-authorized AI-assisted software development tools (coding, test creation, troubleshooting, documentation) with the ability to validate and refine AI outputs for correctness, performance, and security.
• Understanding of responsible AI use in engineering workflows (data sensitivity, secure handling of inputs/outputs, resiliency and security expectations) and ability to guide peers on safe and effective usage.
• Overall knowledge of the Software Development Life Cycle, including design, build, test, release, and run disciplines.
• Solid understanding of agile methodologies and CI/CD, with focus on application resiliency and security practices.
• Proficiency in at least one programming language and ecosystem relevant to building services (e.g., Java/Spring Boot; familiarity with testing practices and frameworks).
• Ability to set and reinforce organization-level practices for reviewing AI-assisted recommendations, escalating uncertain decisions, and maintaining resiliency, security, and auditability outcomes.
• Ability to set and reinforce organization-level practices for reviewing AI-assisted recommendations and escalating uncertain decisions while maintaining resiliency, security, and auditability outcomes.

• Experience creating scalable microservices using Java, Spring Boot, and Kafka for financial services or similarly regulated environments.
• Experience using CI/CD toolsets including Git, Maven, Jenkins, SonarQube, and strong automated testing practices (JUnit, Mockito).
• Experience developing and maintaining deployment, monitoring, and operations automation, including incident response tooling and runbook automation.
• Strong working knowledge of observability patterns and tools (metrics, logs, traces) to troubleshoot complex production issues.
• Experience coaching teams to adopt AI coding assistants (e.g., GitHub Copilot, Cursor, Claude) as standard practice while enforcing secure coding and validation habits.