Lead Software Engineer - Java, Python, Spring Boot, AWS

Lead Software Engineer 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:

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)