Lead Software Engineer-Test Automation , Python /Java , UI , Playwright

📍 Job Overview

Job Title: Lead Software Engineer - Test Automation (Python/Java, UI, Playwright)

Company: JPMorgan Chase & Co.

Location: Plano, TX, United States

Job Type: Full time

Category: Technology / Engineering - Quality Assurance / Test Automation

Date Posted: 2026-08-07

Experience Level: 5+ years

Remote Status: On-site

🚀 Role Summary

• Lead the end-to-end test automation strategy and execution for critical client-facing software within the Commercial and Investment Banking Payments Technology team.

• Drive the adoption and effective utilization of AI-assisted engineering practices to enhance code quality, accelerate delivery, and improve operational outcomes.

• Develop and implement secure, high-quality testing code, and establish robust validation standards across the engineering team.

• Collaborate with cross-functional teams to ensure comprehensive and efficient business flow testing prior to production implementation.

• Contribute to the technical design, development, and troubleshooting of complex software solutions, thinking beyond conventional approaches.

📝 Enhancement Note: This role is a Lead Software Engineer position with a strong focus on test automation. The core responsibilities point towards a senior individual contributor or technical lead role, emphasizing automation strategy, AI adoption, and quality assurance within a financial services context, specifically for client onboarding and payments technology. The "Lead" title suggests mentoring and guiding junior engineers, as well as influencing team best practices.

📈 Primary Responsibilities

• Drive the creation and implementation of comprehensive end-to-end test automation for the Digital Onboarding team, covering both new-to-bank and existing-to-bank client onboarding processes across various client-facing channels.

• Develop secure, high-quality automated testing code, and conduct thorough code reviews and debugging for code written by other team members.

• Champion and lead the team's adoption of enterprise-authorized AI-assisted engineering practices, including AI-assisted code review, refactoring, test strategy acceleration, and incident/root-cause analysis support, to boost code quality and delivery speed.

• Define and enforce consistent validation standards, including secure coding practices, peer reviews, and automated testing methodologies, while promoting the reuse of effective patterns and solutions across the team.

• Leverage knowledge of Software Development Life Cycle (SDLC) tools and enterprise-authorized AI-assisted development and automation capabilities to maximize the value derived from automation initiatives.

• Proactively identify opportunities to eliminate recurring issues through automation or to automate remediation efforts, thereby enhancing the overall operational stability of software applications and systems.

• Lead evaluation sessions with internal stakeholders and technical teams to conduct outcome-oriented reviews of architectural designs, technical capabilities, and their suitability for integration into existing systems and information architecture.

• Provide technical leadership and mentorship to junior engineers and automation testers, guiding them on best practices for test automation, secure coding, and AI tool utilization.

📝 Enhancement Note: The responsibilities clearly indicate a leadership role in test automation, with a significant emphasis on integrating AI tools into the SDLC and promoting best practices for quality and security in a regulated financial environment. The focus on "client-facing channels" and "Digital Onboarding" suggests a direct impact on customer experience and business growth.

🎓 Skills & Qualifications

Education: Formal training or certification on software engineering concepts, coupled with 5+ years of applied experience in software development and testing.

Experience: Hands-on practical experience delivering robust system design, application development, comprehensive testing strategies, and ensuring operational stability of software applications.

Required Skills:

• Advanced proficiency in one or more core programming languages: Python, Java, or Playwright.

• Demonstrated experience in leading the effective use of enterprise-authorized AI-assisted software development tools for coding, code review, test acceleration, and troubleshooting.

• Proven ability to set team expectations for validating AI-generated outputs for correctness, performance, and security.

• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs and outputs, and adherence to resiliency and security expectations.

• Experience coaching engineers on the safe and compliant adoption of AI tools within delivery practices.

• Proficiency across all phases of the Software Development Life Cycle (SDLC).

• Advanced understanding of agile methodologies, including continuous integration (CI) and continuous delivery (CD), application resiliency, and security best practices.

• In-depth knowledge of the financial services industry and its associated information technology systems.

• Practical experience with cloud-native technologies and architectures.

• Ability to work independently, demonstrating resourcefulness and navigating a large, complex organization effectively.

• Experience managing senior stakeholders and leading a team of automation testers, possessing strong influence and negotiation skills, with a willingness to partner on automation initiatives across organizational boundaries. Preferred Skills:

• Payments business knowledge, with a focus on client-facing channels and their associated workflows.

• Strong hands-on test automation experience, either within Quality Assurance (QA) or User Acceptance Testing (UAT) roles.

📝 Enhancement Note: The required skills highlight a blend of deep technical expertise in automation and programming languages, leadership capabilities, and a strong understanding of enterprise AI adoption and financial services regulations. The preference for payments business knowledge and specific QA/UAT automation experience suggests a highly specialized role.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase of end-to-end test automation frameworks developed for complex applications, demonstrating proficiency in Python, Java, or Playwright.

• Examples of automated test suites that have significantly improved test coverage, reduced regression testing time, and increased the speed of deployment for client-facing applications.

• Case studies detailing the implementation of AI-assisted engineering practices within a development or testing workflow, highlighting measurable improvements in code quality, efficiency, or issue resolution.

• Documentation of successful cross-functional collaboration on automation initiatives, illustrating the ability to influence and partner with other teams to achieve shared quality and delivery goals.

• Evidence of contributions to establishing and enforcing validation standards, secure coding practices, and peer review processes within an engineering team. Process Documentation:

• Detailed documentation of automated testing processes, including test case design, script development, execution, and reporting.

• Documentation of workflows for integrating AI tools into the SDLC, including guidelines for prompt engineering, output validation, and responsible AI usage.

• Records of process improvement initiatives, such as the automation of defect triage, root-cause analysis, or recurring issue remediation, demonstrating a commitment to operational stability.

• Examples of how process documentation was used to onboard new team members or to ensure consistent application of standards across the team.

📝 Enhancement Note: For a Lead Software Engineer in Test Automation, a portfolio should prominently feature practical examples of automation frameworks, AI integration, and process improvements. The emphasis on "end-to-end" and "client-facing" applications signifies the need for robust, scalable, and business-impactful automation solutions.

💵 Compensation & Benefits

Salary Range: Based on industry benchmarks for Lead Software Engineers with 5+ years of experience in Plano, TX, the estimated salary range for this role is between $130,000 - $180,000 annually. This estimate considers the specialized skills in test automation, AI integration, and financial services, as well as the Lead level responsibilities.

Benefits:

• Comprehensive health care coverage (medical, dental, vision).

• On-site health and wellness centers to support employee well-being.

• Retirement savings plan (e.g., 401(k)) with potential company match.

• Backup childcare services to support work-life balance.

• Tuition reimbursement programs for continued professional development.

• Mental health support resources and services.

• Financial coaching and advisory services.

• Potential for performance-based bonuses and/or equity awards.

Working Hours: Standard full-time employment typically involves a 40-hour work week. While the role is on-site, JPMorgan Chase & Co. may offer flexible scheduling arrangements where feasible, subject to business needs and team coordination.

📝 Enhancement Note: The salary range is an estimation based on publicly available data for similar roles in the Plano, TX area and the specified experience level. JPMorgan Chase & Co. is a large financial institution, so benefits are typically comprehensive. The "on-site" designation implies a need for local presence, though some flexibility might be available.

🎯 Team & Company Context

🏢 Company Culture

Industry: Financial Services, specifically within Commercial and Investment Banking. This sector is characterized by high regulatory scrutiny, a strong emphasis on security, reliability, and data integrity, and a fast-paced, competitive environment.

Company Size: JPMorgan Chase & Co. is a global financial services firm with tens of thousands of employees worldwide, indicating a large, complex, and well-resourced organization. This scale offers opportunities for broad impact and exposure to diverse technologies and business areas.

Founded: JPMorgan Chase & Co. has a history spanning over 200 years, signifying a long-standing legacy of financial leadership and stability. This deep history often translates to established processes, strong corporate values, and a commitment to long-term growth and innovation.

Team Structure:

• The role sits within the Commercial and Investment Banking - Test Integration and Implementation Payments Technology Team, suggesting a specialized unit focused on quality assurance and deployment for payment-related technologies.

• The team likely includes a mix of software engineers, QA specialists, automation engineers, and potentially business analysts, working collaboratively to ensure the quality and readiness of payment systems.

• As a "Lead" engineer, this role will likely report to a manager or director of engineering and will be responsible for guiding and mentoring other engineers on the team, particularly those focused on test automation. Methodology:

• Data-driven decision-making and rigorous quality assurance are paramount in financial services. Expect a strong focus on metrics, performance analysis, and evidence-based improvements.

• Agile methodologies are standard, emphasizing iterative development, continuous integration, and rapid feedback loops, especially for client-facing products.

• A strong emphasis on secure coding practices, risk management, and compliance with industry regulations will be embedded in all development and testing processes.

Company Website: https://www.jpmorganchase.com/

📝 Enhancement Note: Operating within a global financial institution like JPMorgan Chase & Co. means adhering to stringent security, compliance, and performance standards. The specific team focus on Payments Technology and Digital Onboarding highlights a critical area for client acquisition and retention, requiring robust and reliable systems.

📈 Career & Growth Analysis

Operations Career Level: This position is classified as a "Lead Software Engineer," indicating a senior individual contributor role with technical leadership responsibilities. It sits above a standard Software Engineer level and implies a significant level of autonomy, expertise, and the ability to influence technical direction and team practices. The focus on test automation and AI integration suggests a specialization within the broader software engineering domain.

Reporting Structure: The Lead Software Engineer will likely report to a Manager or Director of Engineering within the Payments Technology division. They will be expected to collaborate closely with product managers, other engineering leads, and potentially business stakeholders to align automation efforts with business objectives. The role also involves managing or mentoring a team of automation testers.

Operations Impact: This role has a direct and significant impact on the success of client onboarding and payment processing systems. By ensuring comprehensive test automation and high-quality software delivery, the Lead Engineer contributes directly to:

• Client Experience: Reducing friction and errors in client onboarding and payment transactions.

• Revenue Generation: Enabling faster and more reliable deployment of new features and products.

• Risk Mitigation: Preventing production defects that could lead to financial losses, reputational damage, or regulatory non-compliance.

• Operational Efficiency: Streamlining testing processes and reducing manual effort.

Growth Opportunities:

• Technical Specialization: Deepen expertise in advanced test automation techniques, AI in engineering, cloud-native architectures, and specific payment technologies.

• Leadership Development: Progress into management roles (e.g., Engineering Manager, Director of QA) or evolve into principal/architect roles focusing on technical strategy and innovation.

• Cross-Functional Mobility: Opportunity to move into product management, program management, or other technology leadership roles within JPMorgan Chase & Co. by leveraging a broad understanding of the business and technology landscape.

• Industry Recognition: Contribute to industry best practices and potentially present at conferences, building a strong professional reputation within the financial technology space.

📝 Enhancement Note: The "Lead" designation is crucial here, implying a trajectory beyond just coding. The emphasis on AI and payments technology positions the candidate for growth in highly sought-after and evolving areas within finance.

🌐 Work Environment

Office Type: This role is designated as "On-site," meaning the primary work location will be at the JPMorgan Chase & Co. office in Plano, TX. This fosters in-person collaboration, team cohesion, and direct access to company resources and facilities.

Office Location(s): 8181 Communications Pkwy Bldg B, Plano, TX 75024. This location is within a business park or corporate campus environment common for large technology and financial firms, likely offering modern amenities and a professional setting.

Workspace Context:

• Collaborative Environment: The on-site nature facilitates spontaneous discussions, brainstorming sessions, and real-time problem-solving with colleagues, crucial for complex technical challenges.

• Tools and Technology: Access to a robust IT infrastructure, including high-performance computing, secure network access, and the latest development and testing tools, will be provided to support the engineering workload.

• Team Interaction: Daily interaction with team members, including fellow engineers, QA specialists, product managers, and potentially business analysts, will be a key aspect of the work environment, promoting knowledge sharing and efficient workflow.

Work Schedule: The standard work schedule is likely Monday to Friday, with a focus on achieving 40 hours per week. While on-site, there might be flexibility in start and end times, subject to team agreements and business needs, to accommodate personal schedules while ensuring coverage for critical business hours and collaborative sessions.

📝 Enhancement Note: The on-site requirement is a key differentiator. For candidates who thrive in a structured, collaborative office environment with direct access to resources and colleagues, this will be appealing. It also suggests a company culture that values in-person interaction for critical team functions.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter or hiring manager will likely conduct an initial phone screen to assess basic qualifications, experience, and cultural fit.

• Technical Interviews (Multiple Rounds): Expect several rounds of technical interviews focusing on:

  • Coding Proficiency: Live coding exercises in Python or Java, testing algorithm design, data structures, and problem-solving skills.
  • Test Automation Concepts: Deep dives into test automation strategies, framework design (e.g., Page Object Model, BDD), API testing, UI testing with Playwright, and performance testing principles.
  • System Design: Scenarios involving designing scalable and robust test automation architectures, considering integration with CI/CD pipelines and various environments.
  • AI in Engineering: Discussion on your experience with AI-assisted tools, how you've validated AI outputs, and your understanding of responsible AI usage in development.
  • Behavioral Questions: Assessing leadership capabilities, problem-solving approaches, collaboration skills, and experience managing stakeholders and teams.

• Portfolio Review/Presentation: A dedicated session where you will present selected projects from your portfolio, detailing your role, the challenges faced, the solutions implemented (especially automation and AI aspects), and the measurable impact.

• Final Round: May involve interviews with senior leadership or key stakeholders to assess strategic thinking and overall fit for the role and company culture.

Portfolio Review Tips:

• Curate Strategically: Select 2-3 impactful projects that best showcase your leadership in test automation, AI integration, and problem-solving.

Prioritize projects with clear business impact and quantifiable results.

• Structure Your Narrative: For each project, clearly articulate:

  • The business problem or objective.
  • Your specific role and responsibilities as a Lead Engineer.
  • The technical challenges encountered.
  • The automation solutions and AI tools employed.
  • Key metrics and outcomes (e.g., reduction in test cycle time, defect escape rate decrease, efficiency gains from AI).
  • Lessons learned and future recommendations.

• Demonstrate Technical Depth: Be prepared to walk through code snippets, explain framework designs, and discuss the intricacies of your automation strategies.

• Highlight Leadership: Emphasize instances where you mentored team members, influenced technical direction, managed stakeholders, or drove process improvements.

• Focus on AI Integration: Clearly articulate how you've leveraged AI tools, the validation processes you implemented, and the benefits realized.

Challenge Preparation:

• Practice Coding: Regularly solve coding problems on platforms like LeetCode, HackerRank, focusing on Python and Java.

• Mock Interviews: Conduct mock interviews with peers or mentors to simulate the interview environment and receive feedback on your technical explanations and behavioral responses.

• Study AI Best Practices: Refresh your knowledge on responsible AI usage, data privacy, and AI validation techniques relevant to software engineering.

• Research JPMorgan Chase & Co.: Understand their business lines (especially CIB and Payments), recent news, and corporate values to tailor your responses and demonstrate genuine interest.

📝 Enhancement Note: The emphasis on a portfolio review and AI integration suggests a need for candidates to clearly articulate not just technical skills but also their ability to lead, innovate, and deliver measurable business value through automation.

🛠 Tools & Technology Stack

Primary Tools:

• Programming Languages: Python and Java are explicitly mentioned as core languages for this role.

• UI Automation Framework: Playwright is a key requirement, indicating a need for expertise in modern browser automation for end-to-end UI testing.

• Test Automation Frameworks: Experience with building and maintaining robust test automation frameworks (e.g., using design patterns like Page Object Model, BDD).

• Version Control: Git is standard for code management.

• CI/CD Tools: Jenkins, GitLab CI, Azure DevOps, or similar for continuous integration and continuous delivery pipelines.

Analytics & Reporting:

• Test Management Tools: Tools like Jira (with plugins like Zephyr/Xray), TestRail, or ALM for test case management, execution tracking, and reporting.

• Reporting Dashboards: Tools like Grafana, Tableau, Power BI, or custom solutions for visualizing test execution status, defect trends, and automation coverage metrics.

• Log Analysis Tools: Splunk, ELK Stack (Elasticsearch, Logstash, Kibana) for analyzing application and test logs to aid in troubleshooting.

CRM & Automation:

• AI-Assisted Engineering Tools: Enterprise-authorized AI coding assistants (e.g., GitHub Copilot, Amazon CodeWhisperer, or proprietary tools) for code generation, refactoring, and test acceleration.

• Collaboration & Project Management: Jira, Confluence, Microsoft Teams for task management, documentation, and team communication.

• Cloud Platforms: Familiarity with cloud environments (AWS, Azure, GCP) is implied by "cloud-native experience," which may be relevant for setting up testing environments or understanding application deployment.

📝 Enhancement Note: The explicit mention of Python, Java, and Playwright, alongside AI-assisted engineering, points to a modern technology stack. Expertise in CI/CD, test management, and logging tools is crucial for integrating automation into the broader SDLC.

👥 Team Culture & Values

Operations Values:

• Quality & Reliability: A deep commitment to delivering high-quality, stable, and reliable software, especially critical in the financial sector. This translates to meticulous testing and a proactive approach to defect prevention.

• Innovation & Efficiency: Embracing new technologies like AI to drive innovation and improve efficiency in development and testing processes. A drive to automate and optimize workflows is expected.

• Collaboration & Partnership: A strong emphasis on working effectively across teams and with stakeholders to achieve shared goals. Open communication and a willingness to support cross-functional initiatives are key.

• Security & Compliance: Adherence to strict security protocols and regulatory compliance standards in all aspects of software development and testing. A thorough understanding of data sensitivity and responsible AI usage is vital.

• Continuous Improvement: A mindset focused on learning, adapting, and continuously enhancing processes, tools, and skills to stay ahead in a dynamic industry.

Collaboration Style:

• Cross-Functional Integration: Expect to work closely with development teams, product managers, business analysts, and potentially operations and compliance teams to ensure comprehensive test coverage and alignment with business objectives.

• Process Review Culture: A willingness to participate in regular reviews of development and testing processes, providing constructive feedback and actively contributing to improvements.

• Knowledge Sharing: An environment that encourages sharing best practices, lessons learned, and technical expertise through code reviews, documentation, and team discussions. This is particularly important for disseminating knowledge about AI tools and automation techniques.

📝 Enhancement Note: The culture at a major financial institution like JPMorgan Chase & Co. will likely be professional, results-oriented, and highly focused on compliance and security. The emphasis on AI and innovation suggests a forward-thinking aspect within this structured environment.

⚡ Challenges & Growth Opportunities

Challenges:

• Complexity of Financial Systems: Navigating the intricate and highly regulated systems within investment banking and payments technology requires deep domain knowledge and meticulous attention to detail.

• Pace of Innovation vs. Stability: Balancing the need for rapid feature delivery and adoption of new technologies (like AI) with the paramount requirement for system stability, security, and regulatory compliance.

• AI Integration and Validation: Effectively integrating AI-assisted tools into existing workflows while establishing robust processes to validate AI outputs, manage data sensitivity, and ensure responsible usage.

• Cross-Organizational Dependencies: Coordinating automation efforts and testing across multiple teams and systems within a large organization, requiring strong influencing and communication skills.

• Keeping Pace with Technology: Continuously learning and adapting to new automation tools, programming languages, AI advancements, and evolving cloud-native practices.

Learning & Development Opportunities:

• AI in Engineering Specialization: Opportunities to become a subject matter expert in leveraging AI for software development and testing, potentially leading internal training or workshops.

• Advanced Automation Techniques: Pursuing training and certifications in cutting-edge test automation frameworks, performance testing, security testing, and API automation.

• Payments Technology Domain Expertise: Deepening knowledge of the payments industry, including client onboarding processes, transaction flows, and regulatory landscapes.

• Leadership and Mentorship Programs: Engaging in leadership development programs designed to hone skills in team management, strategic planning, and stakeholder engagement.

• Cloud Certifications: Pursuing certifications related to cloud platforms (AWS, Azure, GCP) to enhance cloud-native development and testing capabilities.

📝 Enhancement Note: The challenges highlight the critical nature of the role and the need for continuous learning. The growth opportunities are well-aligned with current industry trends in AI, cloud, and specialized financial technology.

💡 Interview Preparation

Strategy Questions:

• Automation Strategy: "Describe how you would design and implement an end-to-end test automation strategy for a complex client onboarding platform, considering scalability, maintainability, and integration with CI/CD."

  • Preparation: Focus on modular framework design, risk-based testing approaches, API vs. UI automation balance, data management strategies, and reporting mechanisms.

• AI Tool Implementation: "How would you introduce and ensure the responsible adoption of an AI-assisted coding tool within a team of software engineers? What are the key validation steps you would implement?"

  • Preparation: Discuss pilot programs, training, clear guidelines on AI usage, data security protocols, output verification processes, and mechanisms for feedback.

• Problem Solving & Debugging: "Walk me through a challenging bug you encountered in a complex system. How did you approach diagnosing and resolving it, and what steps did you take to prevent its recurrence?"

  • Preparation: Use the STAR method (Situation, Task, Action, Result). Emphasize your systematic approach, the tools used, collaboration, and any automation implemented to prevent recurrence.

Company & Culture Questions:

• Role Alignment: "Why are you interested in this Lead Software Engineer role at JPMorgan Chase & Co., and what specifically about our Payments Technology team appeals to you?"

  • Preparation: Research the CIB division, Payments Technology, and express enthusiasm for the challenges of financial services, AI integration, and client-facing solutions.

• Team Collaboration: "Describe your experience working with cross-functional teams. How do you ensure alignment and effective collaboration, especially when dealing with differing priorities?"

  • Preparation: Provide examples of successful collaborations, communication strategies, and conflict resolution approaches.

• Impact Measurement: "How do you measure the success and business impact of your test automation efforts?"

  • Preparation: Discuss key metrics like test execution time reduction, defect escape rates, automation ROI, release cycle speed, and qualitative feedback on system stability.

Portfolio Presentation Strategy:

• Start with Impact: Begin your presentation by clearly stating the business problem and the quantifiable impact of your project.

• Showcase Leadership: Highlight your role in driving the automation strategy, mentoring team members, and influencing technical decisions.

• Detail Technical Implementation: Clearly explain the architecture of your automation framework, the specific tools (Python, Java, Playwright, AI tools) and techniques used, and why they were chosen.

• Demonstrate AI Integration: If applicable, dedicate a section to how you integrated and validated AI tools, showcasing the process and results.

• Be Ready for Deep Dives: Anticipate detailed questions about your code, design choices, and decision-making processes.

📝 Enhancement Note: The interview preparation focuses on demonstrating technical leadership, strategic thinking, practical application of automation and AI, and alignment with the rigorous demands of the financial services industry.

📌 Application Steps

To apply for this Lead Software Engineer position:

• Submit your application through the provided Oracle Cloud HCM link: https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/job/210777012

• Tailor Your Resume: Customize your resume to highlight experience with Python, Java, Playwright, test automation frameworks, CI/CD, AI-assisted engineering, and financial services. Quantify achievements with metrics wherever possible.

• Prepare Your Portfolio: Curate 2-3 key projects that best demonstrate your leadership in test automation, AI integration, and problem-solving. Be ready to present these with a clear narrative of challenges, solutions, and impact.

• Practice Interview Questions: Rehearse answers to common technical, behavioral, and situational questions, focusing on demonstrating your expertise and leadership potential. Practice coding exercises and system design scenarios.

• Research JPMorgan Chase & Co.: Familiarize yourself with the company's mission, values, and specific business units like Commercial Investment Banking and Payments Technology to articulate your interest and cultural fit.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.