Java/Python Lead Software Engineer

JPMorgan Chase & Co.; Plano (TX); On-site; USD 140,000 - 210,000; Full time

Job summary

JPMorgan Chase & Co. in Plano seeks a Lead Software Engineer to drive technical leadership, architecture, and hands-on delivery across multiple technologies within the Data Technology space of Consumer & Community Banking (CCB).

You will guide design decisions for cloud-native AWS services, APIs, and event-driven components while advancing secure coding, automated testing, and AI-assisted development practices across teams.

Qualifications

• 5+ years of applied software engineering experience.
• Hands-on system design, development, testing, and production stability for services.
• Advanced in Java, Python, or Go with strong AWS experience.
• Experience organizing Terraform workspaces and infrastructure-as-code.
• Experience designing microservices and backend data models.

Responsibilities

• Provides technical guidance to engineering teams, contractors, and vendors.
• Designs and develops secure, high-quality production code; performs code reviews.
• Leads system design and implementation for cloud-native services on AWS (APIs, services, event-driven components).
• Drives decisions influencing product design, functionality, and operations.
• Drives adoption of AI-assisted engineering practices to improve code quality and delivery speed.
• Establishes validation standards for AI-assisted workflows and promotes reuse of patterns.

Skills

Java

Python

Go

AWS

Terraform

Tools

Docker

CI/CD

Kubernetes

Job description

As a Lead Software Engineer at JPMorganChase within Consumer & Community Banking (CCB) in the Data Technology space, you will be part of an agile team building and delivering secure, stable, and scalable technology products. You will drive significant business impact through technical leadership, architecture and design influence, and hands‑on delivery across multiple technologies and applications.

Job Responsibilities

• Provides technical guidance and direction to support the business and its engineering teams, contractors, and vendors.
• Designs and develops secure, high‑quality production code; reviews, debugs, and raises the engineering bar through strong code review practices.
• Leads system design and implementation for cloud‑native services on AWS, including APIs, standalone services, and event‑driven components.
• Drives decisions that influence product design, application functionality, and technical operations and processes.
• Drives adoption and governance of approved AI‑assisted engineering practices to improve code quality, delivery speed, and operational outcomes (e.g., AI‑assisted code review/refactoring, test acceleration, release readiness, incident/root‑cause analysis).
• Establishes measurable validation standards for AI‑assisted workflows (secure coding, peer review, automated testing) and promotes reuse of proven patterns and automation within the SDLC/toolchain.
• Applies SDLC toolchain expertise (CI/CD, testing, IaC, observability) to improve reliability, delivery throughput, and operational excellence.
• Serves as a function‑wide subject matter expert in one or more areas of focus and contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices.

Required Qualifications, Capabilities, and Skills

• Formal training or certification in software engineering concepts and 5+ years of applied experience.
• Hands‑on experience delivering system design, application development, testing, and operational stability for production services.
• Advanced in one or more programming languages (Java, Python, or Go) with strong AWS experience.
• Strong experience with AWS services to host APIs, run applications, enable inter‑application messaging, and implement event‑driven services.
• Experience organizing Terraform workspaces and developing Terraform code (infrastructure as code).
• Experience designing and developing microservices and backend services.
• Experience designing backend data models and working with databases (relational and/or NoSQL).
• Demonstrated experience leading effective use of enterprise‑authorized AI‑assisted software development tools within the work environment, including setting team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows (data sensitivity, secure handling of inputs/outputs, resiliency and security expectations) and experience coaching engineers/leads on compliant usage patterns and controls.
• Ability to tackle complex design and functionality problems independently with limited oversight.

Preferred Qualifications, Capabilities, and Skills

• Experience with messaging/eventing systems (e.g., Kafka, SNS/SQS, Kinesis, MQ).
• Experience with Docker/containerization best practices and CI/CD pipeline tooling.
• Understanding of security best practices and secure coding principles.
• Experience with test‑driven development (TDD), automated testing frameworks, and modern API design patterns.