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Software Developer Engineer Test [AQ-12373]

Aquent Talent

Austin, TX 78716

~ 39 min OnsiteHealth InsurancePaid Time OffRetirement Benefit

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 platforms such as Kubernetes, Docker, GCP, AWS, Azure, or comparable 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 such as GitHub, GitLab, Azure DevOps, Jira, Rally, Confluence, or comparable platforms.
Working experience or exposure to messaging, streaming, or event-driven technologies such as Kafka, IBM MQ, RabbitMQ, or 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.