Software Developer Engineer Test

Aquent is proud to partner with a leading enterprise in the financial services industry, a company dedicated to innovation and excellence in delivering robust, high-volume solutions that impact millions. This is an exceptional opportunity to join a team that values cutting-edge technology, quality engineering, and the responsible application of AI to redefine how software is built and tested. Your contributions will directly enhance the reliability, performance, and security of critical applications, shaping the future of financial technology.

Step into a pivotal role where your expertise in quality engineering and your passion for artificial intelligence will converge to drive significant impact. As a key contributor, you will be at the forefront of defining and executing technology-agnostic quality engineering practices across modern application stacks. You'll collaborate closely with developers, architects, product owners, and operations teams, playing a crucial role in elevating test automation, boosting release confidence, and enhancing engineering productivity. This is your chance to lead the charge in applying AI-assisted SDLC practices responsibly, ensuring the highest standards of quality and innovation, directly influencing the stability and innovation of platforms serving millions.

What You'll Do

• Partner with product owners, developers, architects, and cross-functional teams to translate business and technical requirements into comprehensive test strategies, test cases, automation coverage, and release validation plans.
• Design, develop, and maintain scalable automated test frameworks and test suites across various layers, including UI, API, service, integration, data, event-driven, end-to-end, regression, performance, and deployment validation.
• Drive quality engineering best practices by integrating automated tests into CI/CD pipelines, significantly improving test reliability, reducing manual validation effort, and enabling faster, safer releases.
• Validate distributed, high-volume, and event-driven systems, ensuring message flows, data integrity, service contracts, resilience, observability, operational readiness, and robust failure recovery scenarios.
• Leverage AI-assisted engineering tools to enhance test design, accelerate automation development, improve test coverage, streamline documentation, bolster regression support, facilitate defect analysis, and troubleshoot efficiently, all while maintaining ownership for correctness and quality.
• Apply prompt engineering, reusable instructions, spec-driven workflows, and agentic concepts to accelerate quality engineering activities in a responsible, reviewable, and measurable manner.
• Create and maintain essential quality artifacts, including test plans, automation strategy, traceability matrices, defect analysis reports, validation evidence, release readiness summaries, and audit-ready documentation.
• Collaborate with globally distributed teams, influencing quality outcomes across the entire SDLC through automation-first thinking, risk-based testing, engineering rigor, and a commitment to continuous improvement.

Required Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related technical field, or equivalent practical experience.
• 8 years of experience in software testing, test automation, software development, or quality engineering for enterprise applications in highly available, high-volume environments.
• Hands-on experience designing, developing, and maintaining automated test frameworks using one or more modern programming languages and test automation ecosystems.
• Strong experience with API testing, UI automation, service validation, integration testing, end-to-end testing, regression automation, test data validation, and release validation practices.
• Experience validating cloud-native, containerized, distributed, or service-based applications deployed on leading enterprise platforms.
• Experience with SQL or NoSQL databases, including test data creation, data validation, query-based verification, and quality checks across structured or semi-structured data.
• Strong understanding of object-oriented programming, scripting, algorithms, data structures, debugging practices, service contracts, and automation design principles.
• Experience with CI/CD pipeline integration, source control, work tracking, and collaboration tools on comparable enterprise platforms.
• Working experience or exposure to messaging, streaming, or event-driven technologies, including cloud pub/sub services.
• Experience applying BDD, TDD, ATDD, risk-based testing, shift-left testing, quality gates, and modern quality engineering practices across the SDLC.
• Demonstrated hands-on experience using Generative AI coding assistants across SDLC workflows, including test generation, automation development, refactoring, unit testing, regression support, code reviews, scripting, troubleshooting, and documentation.
• Practical familiarity with AI-assisted engineering tools in IDE, CLI, or workflow-based environments.
• Working knowledge of Generative AI concepts, responsible AI-assisted engineering practices, prompt engineering, reusable prompts, custom instructions, and AI-augmented SDLC workflows.
• Ability to use AI tools while maintaining strong engineering judgment, code review rigor, validation discipline, data protection awareness, and quality accountability.
• Experience applying automation and AI-driven approaches to improve testing workflows, delivery processes, operational quality outcomes, and modernization initiatives.
• Excellent problem-solving, critical thinking, communication, and decision-making skills, with the ability to work independently in a fast-paced, team-oriented environment.
• Understands financial services domain capabilities and operations, with experience in the financial services industry.
• Communicates clearly and effectively, with proven ability to guide and collaborate with engineers in a team-oriented environment.
• Brings a collaborative mindset and bias for action, effectively partnering with developers, architects, product owners, and adjacent teams to drive outcomes.

Preferred Qualifications

• Experience as a Software Development Engineer in Test on an Agile Scrum, Kanban, or scaled Agile team.
• Experience with performance, reliability, resiliency, chaos, observability, or production-readiness testing for high-volume distributed platforms.
• Experience in the brokerage, banking, wealth management, capital markets, or broader financial services domain.
• Experience defining automation strategy, framework standards, coding guidelines, quality metrics, and release readiness criteria across multiple teams or platforms.
• Proficiency in creating automation design documentation, functional and technical validation notes, test process documentation, runbooks, and production or test environment documentation.
• Exposure to AI/ML implementation concepts, Large Language Models, agentic workflows, Retrieval-Augmented Generation, or AI-assisted quality engineering practices.
• Experience mentoring engineers or influencing teams on quality engineering, test automation, AI-assisted SDLC adoption, and continuous improvement practices.

About Aquent Talent:

Aquent Talent connects the best talent in marketing, creative, and design with the world's biggest brands.

Our eligible talent get access to amazing benefits like subsidized health, vision, and dental plans, paid sick leave, and retirement plans with a match. We also offer free online training through Aquent Gymnasium. More information on our awesome benefits!

Aquent is an equal-opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics. We're about creating an inclusive environment-one where different backgrounds, experiences, and perspectives are valued, and everyone can contribute, grow their careers, and thrive.