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 organization is at the forefront of redefining how software is built and tested, leveraging cutting-edge technology and responsible AI to enhance the reliability, performance, and security of critical applications that serve millions globally.

This is an exceptional opportunity to join a team that is not just building software, but shaping the future of financial technology, and your contributions will directly influence the stability and innovation of platforms serving millions.

We are seeking a highly skilled and passionate individual to 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. This is your chance to lead the charge in applying AI-assisted SDLC practices responsibly, ensuring the highest standards of quality and innovation, elevating test automation, boosting release confidence, and enhancing engineering productivity across critical systems.

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.

Must-Have 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 No
  
  SQL databases, including test data creation, data validation, query-based verification, and quality checks across structured or semi-structured data.
• Strong…