JP Morgan Chase

Runs a consumer bank and an investment bank

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

Backend EngineeringConfirmed live in the last 24 hours

Full-timePlano, TX, USANo salary listedIn-person

About the Job

Requirements

Formal training or certification in computer science or software engineering concepts and at least 5 years of applied experience.
At least 10 years of hands-on software development experience in large-scale distributed systems, primarily using Java, modern Java with Spring Boot microservices, and Python.
Hands-on practical experience in system design, application development, testing, and operational stability.
Hands-on experience using enterprise-authorized artificial intelligence-assisted software development tools for coding, test creation, troubleshooting, or documentation, with the ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
Understanding of responsible artificial intelligence use in engineering workflows, including data sensitivity considerations, secure handling of inputs and 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 or microservices architecture.
Strong experience with Apache Spark and SQL, including big data processing focused on performance and optimization.
Experience with Kubernetes orchestration, including building, deploying, and operating production services.
Experience with Amazon Web Services services and tooling, including Terraform, EMR, EKS or ECS, Lambda, RDS, and S3.
Experience with log analytics and observability tools, including Splunk, AWS CloudWatch, or Datadog.
Solid understanding of agile methodologies, continuous integration and continuous delivery, application resiliency, and security.

Responsibilities

Execute software solutions, design, development, and technical troubleshooting while applying unconventional approaches to build solutions and break down technical problems.
Leverage enterprise-authorized artificial intelligence coding-assistance tools to improve code quality, delivery speed, and productivity across complex deliverables such as code generation, refactoring, unit-test creation, and documentation; validate outputs through peer review, automated testing, and secure coding standards, and contribute reusable patterns to improve team effectiveness.
Apply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized artificial intelligence-assisted development and automation capabilities, to improve the value realized by automation.
Design, implement, and deploy secure, resilient, highly scalable, fault-tolerant services that integrate with enterprise systems while meeting functional, performance, scalability, security, governance, and auditability requirements.
Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets to support continuous improvement of software applications and systems.
Identify hidden problems and patterns in data and use those insights to improve coding hygiene and system architecture.
Apply backend infrastructure patterns such as load balancing and autoscaling, and implement monitoring and alerting for performance, scalability, availability, and reliability.
Drive consistent validation standards, including secure coding, peer review, and automated testing, and promote reuse of effective patterns across the team.
Lead and mentor junior team members in a high-pressure delivery environment, manage multiple deliverables across business groups, and strengthen stakeholder relationships.
Define and implement guardrails and evaluation approaches for agentic artificial intelligence used in production applications while meeting quality, safety, latency, and cost requirements.
Collaborate with line-of-business users, subject-matter experts, architects, database administrators, and system administrators to design solutions, manage enhancements, and resolve issues.

Desired Qualifications

Contribute to software engineering communities of practice and events that explore new and emerging technologies.
Experience with Scala.
Experience with or exposure to Snowflake or Databricks cloud platforms.
Experience with an Open Table Format such as Iceberg.

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)

About the Company

JP Morgan Chase

Runs a consumer bank and an investment bank

JPMorgan Chase runs the largest bank in the United States, which serves households and small businesses as Chase and large companies, governments, and investors as J.P. Morgan. During the 2008 financial crisis it bought the failing investment bank Bear Stearns and lender Washington Mutual, and in 2023 it took over First Republic Bank after regulators seized it. Chase takes deposits and earns interest on credit cards, mortgages, and car loans, while the investment side earns fees for advising on mergers, raising money for companies, trading stocks and bonds, and managing wealth. Formed in a 2000 merger, JPMorgan Chase traces its roots to 1799 and is based in New York City.

Company size: 10,001+
Company stage: IPO
Headquarters: New York City, New York
Founded: 1799

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