Lead Software Engineer - Python/Automation

JPMorgan Chase & Co.; Plano (TX); On-site; USD 140,000 - 200,000; Full time

Job summary

JPMorgan Chase & Co. in Plano, TX, seeks a Lead Software Engineer to drive design, development, and delivery of trusted, scalable storage technology within the Corporate Sector - Infrastructure Platforms.

As a core technical contributor, you will mentor engineers, advance AI-assisted development practices, and ensure secure, observable production software across distributed systems. You will collaborate with product, risk, and operations teams to meet business goals, while championing

Qualifications

• Formal training or certification in software engineering.
• 5+ years of practical software development experience.
• Strong in system design, production operations and stability.

Responsibilities

• Develop and troubleshoot software solutions across the storage product domain.
• Design and deliver secure, high-quality production code in Python.
• Lead AI-assisted engineering practices and set validation standards.
• Collaborate with cross-functional teams to refine requirements and architectures.
• Mentor junior engineers and promote engineering standards.

Skills

Distributed systems

Python

Java

CI/CD

Cloud-native

AI-assisted engineering

Secure coding

Root-cause analysis

Mentoring

Education

Software engineering concepts training

5+ years applied experience

Tools

RabbitMQ

CockroachDB

Docker

Kubernetes

AWS

REST API design

FastAPI

Django

Job description

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 JPMorgan Chase within the Corporate Sector - Infrastructure Platforms - Storage team, 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 creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Design and deliver solutions that address complex business and technical challenges across the storage product domain
• Builds secure, high-quality production software in Python, applying best practices in testing, code review, observability, and performance tuning
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
• 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
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies and partner with cross-functional stakeholders (engineering, product, operations, risk/security) to refine requirements, propose architectures, and deliver outcomes aligned to customer needs and business goals
• Debug and troubleshoot complex issues in distributed systems with leading root-cause analysis and drive long-term fixes
• Mentors junior engineers through coaching, pairing, reviews, and knowledge sharing—raising engineering standards across the team.
• Adds to team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Demonstrated strength in system design, application development, testing strategies, and production operations/stability
• Advanced in one or more programming language(s) and framework(s) (e.g., Python, Java, Fast API, Django, Rest API design, Containers, etc.)
• Experience with distributed systems and messaging, such as RabbitMQ (or equivalent)
• Experience with modern data stores such as Cockroach DB (or equivalent distributed SQL/NoSQL systems).
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations with experience coaching engineers on safe, compliant and adoption within delivery practices
• Proficient in all aspects of the Software Development Life Cycle from requitements and design through production support and continuous enhancement
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security, including automation (testing, deployment practices, secure coding, least privilege, incident response, SLOs/SLIs)
• Practical cloud-native experience (e.g., containerization, infrastructure-as-code concepts, managed services), including exposure to AWS

Preferred qualifications, capabilities, and skills

• Experience with storage systems, infrastructure technologies, or platform engineering domains
• Exposure to modern and emerging technologies (e.g., event-driven architectures, service mesh, zero trust patterns, AI-assisted engineering)
• Experience modernizing legacy systems and improving reliability at scale