Lead Software Engineer - Java, Python, Spring Boot, AWS
JPMorgan Chase · Plano, United States · 13d ago
Staff / Lead / PrincipalOn-siteSoftware Engineering
Our Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You’ll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda.
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Lead Software Engineer at JPMorganChase within the Corporate Technology, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities:
As a Lead Software Engineer at JPMorganChase within the Corporate Technology, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting 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
- 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
- Designs, implements, and deploys secure, resilient, highly scalable, fault-tolerant services that integrate with enterprise systems; ensures functional, performance, scalability, security, governance, and auditability requirements are met
- 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
- Applies backend infrastructure patterns (e.g., load balancing, autoscaling) and implements monitoring/alerting for performance, scalability, availability, and reliability
- Drives consistent validation standards (secure coding, peer review, automated testing) and promotes reuse of effective patterns across the team
- Leads and mentors junior team members in a high-pressure delivery environment; manages multiple deliverables across business groups and strengthens stakeholder relationships
- Defines and implements guardrails and evaluation approaches for agentic AI used in production applications to deliver business value while meeting quality, safety, latency, and cost requirements
- Collaborates with LOB users, SMEs, architects, DBAs, and system administrators to design solutions, manage enhancements, and resolve issues
Required qualifications, capabilities, and skills:
- Formal training or certification in computer science or software engineering concepts and 5+ years of applied experience
- 10+ years of hands-on software development experience in large-scale distributed systems, primarily in Java, modern Java/Spring Boot microservices, and Python
- Hands-on practical experience in system design, application development, testing, and operational stability
- 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
- Strong experience with REST APIs and service-oriented / microservices architecture
- Strong experience with Spark and SQL; big data processing with focus on performance and optimization
- Kubernetes orchestration experience (building, deploying, and operating production services)
- Experience with AWS services and tooling (e.g., Terraform, EMR, EKS/ECS, Lambda, RDS, S3)
- Experience with log analytics / observability tools (e.g., Splunk, AWS CloudWatch, Datadog)
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Preferred qualifications, capabilities, and skills:
- 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
- Excellent oral and written communication, and problem-solving skills
- Experience with Scala programming language
- Experience with or exposure to Snowflake or Databricks cloud platforms
- Experience with Open Table Format like Iceberg (preferred)