J.P. Morgan
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As an AI Test Automation Engineer at JPMorgan Chase within the Corporate Sector, you will play a key role in advancing our software engineering practices. You will actively contribute to the organizational design, development, and implementation of intelligent automation solutions, collaborating with senior leaders to drive innovation and continuous improvement. This role offers the opportunity to take ownership of automation initiatives, experiment with emerging AI/ML testing methodologies, and help shape the future of quality engineering within the organization. You will be a proactive contributor to organizational transformation, not just a support function. This role provides significant opportunities for professional growth, mentorship from senior leaders, and exposure to cutting-edge automation and AI/ML technologies
Job responsibilities:
Ability to design, build, and enhance automation frameworks, leveraging AI/ML for smarter, more resilient testing. Ability to enhance automation frameworks and testing processes, with a focus on predictive analysis, test case generation, and self-healing mechanisms. Validate performance, reliability, and compliance of AI-driven solutions and agentic workflows. Strong understanding of BDD/TDD (Behavior Driven Development/Test Driven Development). Hands-on experience with automation frameworks such as Playwright, Cucumber, Cypress, Selenium, and JUnit. Experience integrating automated tests into CI/CD pipelines using tools like Jenkins, Maven, or Gradle. Experience with cloud technologies, Docker, and Kubernetes is a plus. Willingness to experiment with new tools and approaches, contributing ideas for continuous improvement. Required qualifications, capabilities, and skills:
Formal training or certification on software engineering concepts and 3+ years applied experience. 5+ years of relevant experience as a Software Developer or Software Developer in Test with expertise in at least one programming language (e.g. Java, Python, JavaScript). 3+ years of experience with non-functional testing (Performance, Resilience, etc.). Experience with AI testing tools and intelligent systems. Creating and promoting automated testing standards, methodologies, and guidelines for enterprise applications. Excellent interpersonal, written, and verbal communication skills, with the ability to influence and manage multiple stakeholders. Collaborating with firmwide testing frameworks teams, architects, engineering directors, and senior application engineers to integrate business and technology requirements into automated testing approaches Strong problem-solving and analytical skills and ability to use data and metrics to assess the effectiveness of automation and AI-driven testing solutions. Ability to run and manage POCs to assess the feasibility and impact of new test automation technologies and methodologies, ensuring alignment with business goals and technical requirements. Work collaboratively with application teams, architects, and AI/ML specialists to integrate business and technology requirements into automated testing strategies. Empathy and passion for improving productivity and experience for engineering teams by fostering an environment conducive to innovative AI development. Preferred qualifications, capabilities, and skills:
Demonstrated eagerness to learn, grow, and adapt to new technologies and methodologies. Ability to quickly learn new tools and techniques focused on Automation. Ability to take initiative and drive results in a fast-paced, dynamic environment. Ability to multi-task and work on different priorities under tight deadlines. Good knowledge of industry-wide technology trends and best practices in AI/ML frameworks.
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Ability to design, build, and enhance automation frameworks, leveraging AI/ML for smarter, more resilient testing. Ability to enhance automation frameworks and testing processes, with a focus on predictive analysis, test case generation, and self-healing mechanisms. Validate performance, reliability, and compliance of AI-driven solutions and agentic workflows. Strong understanding of BDD/TDD (Behavior Driven Development/Test Driven Development). Hands-on experience with automation frameworks such as Playwright, Cucumber, Cypress, Selenium, and JUnit. Experience integrating automated tests into CI/CD pipelines using tools like Jenkins, Maven, or Gradle. Experience with cloud technologies, Docker, and Kubernetes is a plus. Willingness to experiment with new tools and approaches, contributing ideas for continuous improvement. Required qualifications, capabilities, and skills:
Formal training or certification on software engineering concepts and 3+ years applied experience. 5+ years of relevant experience as a Software Developer or Software Developer in Test with expertise in at least one programming language (e.g. Java, Python, JavaScript). 3+ years of experience with non-functional testing (Performance, Resilience, etc.). Experience with AI testing tools and intelligent systems. Creating and promoting automated testing standards, methodologies, and guidelines for enterprise applications. Excellent interpersonal, written, and verbal communication skills, with the ability to influence and manage multiple stakeholders. Collaborating with firmwide testing frameworks teams, architects, engineering directors, and senior application engineers to integrate business and technology requirements into automated testing approaches Strong problem-solving and analytical skills and ability to use data and metrics to assess the effectiveness of automation and AI-driven testing solutions. Ability to run and manage POCs to assess the feasibility and impact of new test automation technologies and methodologies, ensuring alignment with business goals and technical requirements. Work collaboratively with application teams, architects, and AI/ML specialists to integrate business and technology requirements into automated testing strategies. Empathy and passion for improving productivity and experience for engineering teams by fostering an environment conducive to innovative AI development. Preferred qualifications, capabilities, and skills:
Demonstrated eagerness to learn, grow, and adapt to new technologies and methodologies. Ability to quickly learn new tools and techniques focused on Automation. Ability to take initiative and drive results in a fast-paced, dynamic environment. Ability to multi-task and work on different priorities under tight deadlines. Good knowledge of industry-wide technology trends and best practices in AI/ML frameworks.
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