Overview Placement Type:

Temporary Salary:

$54-60 Hourly W2

Start Date:

Aug 28, 2026 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. About the

Role:

Senior Software Development Engineer in Test with AI 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 Senior Software Development Engineer in Test, 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. 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.\nDesign, 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.\nDrive 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.\nValidate distributed, high-volume, and event-driven systems, ensuring message flows, data integrity, service contracts, resilience, observability, operational readiness, and robust failure recovery scenarios.\nLeverage 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.\nApply prompt engineering, reusable instructions, spec-driven workflows, and agentic concepts to accelerate quality engineering activities in a responsible, reviewable, and measurable manner.\nCreate and maintain essential quality artifacts, including test plans, automation strategy, traceability matrices, defect analysis reports, validation evidence, release readiness summaries, and audit-ready documentation.\nCollaborate 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. What You'll Bring Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related technical field, or equivalent practical experience.\n8+ years of experience in software testing, test automation, software development, or quality engineering for enterprise applications in highly available, high-volume environments.\nHands-on experience designing, developing, and maintaining automated test frameworks using one or more modern programming languages and test automation ecosystems.\nStrong experience with API testing, UI automation, service validation, integration testing, end-to-end testing, regression automation, test data validation, and release validation practices.\nExperience validating cloud-native, containerized, distributed, or service-based applications deployed on platforms such as Kubernetes, Docker, GCP, AWS, Azure, or comparable enterprise platforms.\nExperience with SQL or NoSQL databases, including test data creation, data validation, query-based verification, and quality checks across structured or semi-structured data.\nStrong understanding of object-oriented programming, scripting, algorithms, data structures, debugging practices, service contracts, and automation design principles.\nExperience with CI/CD pipeline integration, source control, work tracking, and collaboration tools such as GitHub, GitLab, Azure DevOps, Jira, Rally, Confluence, or comparable platforms.\nWorking experience or exposure to messaging, streaming, or event-driven technologies such as Kafka, IBM MQ, RabbitMQ, cloud pub/sub services, or comparable platforms.\nExperience applying BDD, TDD, ATDD, risk-based testing, shift-left testing, quality gates, and modern quality engineering practices across the SDLC.\nDemonstrated 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.\nPractical familiarity with AI-assisted engineering tools in IDE, CLI, or workflow-based environments.\nWorking knowledge of Generative AI concepts, responsible AI-assisted engineering practices, prompt engineering, reusable prompts, custom instructions, and AI-augmented SDLC workflows.\nAbility to use AI tools while maintaining strong engineering judgment, code review rigor, validation discipline, data protection awareness, and quality accountability.\nExperience applying automation and AI-driven approaches to improve testing workflows, delivery processes, operational quality outcomes, and modernization initiatives.\nExcellent problem-solving, critical thinking, communication, and decision-making skills, with the ability to work independently in a fast-paced, team-oriented environment.\nUnderstands financial services domain capabilities and operations, with experience in the financial services industry.\nCommunicates clearly and effectively, with proven ability to guide and collaborate with engineers in a team-oriented environment.\nBrings a collaborative mindset and bias for action, effectively partnering with developers, architects, product owners, and adjacent teams to drive outcomes. What Will Set You Apart Experience as a Software Development Engineer in Test on an Agile Scrum, Kanban, or scaled Agile team.\nExperience with performance, reliability, resiliency, chaos, observability, or production-readiness testing for high-volume distributed platforms.\nExperience in the brokerage, banking, wealth management, capital markets, or broader financial services domain.\nExperience defining automation strategy, framework standards, coding guidelines, quality metrics, and release readiness criteria across multiple teams or platforms.\nProficiency in creating automation design documentation, functional and technical validation notes, test process documentation, runbooks, and production or test environment documentation.\nExposure to AI/ML implementation concepts, Large Language Models, agentic workflows, Retrieval-Augmented Generation, or AI-assisted quality engineering practices.\nExperience mentoring engineers or influencing teams on quality engineering, test automation, AI-assisted SDLC adoption, and continuous improvement practices.

Please note:

This position is available on a W-2 employment basis only and is not open to Corp-to-Corp (C2C) arrangements. The client is also unable to provide employment-based visa sponsorship or transfers for this role. #LI-LP1

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. 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. 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