Senior AI-Driven SDET: Automation & Quality Leader

Spectraforce Technologies

Austin (TX)

On-site

USD 140,000 - 210,000

Full time

14 days+

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Job summary

Spectraforce Technologies in Austin/Southlake, TX, is seeking a Senior Software Development Engineer in Test with AI to lead quality engineering across stacks and enable AI-assisted SDLC practices. You will partner with developers, architects, product owners, and operations to expand automation, improve release confidence, and drive testing strategy in a fast-paced environment.

This role emphasizes testing across UI, API, data, and distributed systems, with hands-on framework development and

Qualifications

Bachelor's degree in Computer Science or related 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 PCF, Kubernetes, Docker, GCP, AWS, Azure, or comparable enterprise platforms.
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, cloud pub/sub services, or comparable platforms.

Responsibilities

Partner with product owners, developers, architects, and cross-functional teams to understand business and technical requirements and translate them into comprehensive test strategies, test cases, automation coverage, and release validation plans.
Design, develop, and maintain scalable automated test frameworks and test suites across UI, API, service, integration, data, event-driven, end-to-end, regression, performance, and deployment validation layers.
Drive quality engineering best practices by integrating automated tests into CI/CD pipelines, improving test reliability, reducing manual validation effort, and enabling faster, safer releases.
Validate distributed, high-volume, and event-driven systems, including message flows, data integrity, service contracts, resilience, observability, operational readiness, and failure recovery scenarios.
Use AI-assisted engineering tools such as GitHub Copilot or equivalent to improve test design, automation development, test coverage, documentation, regression support, defect analysis, troubleshooting, and engineering productivity 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 quality artifacts including test plans, automation strategy, traceability, defect analysis, validation evidence, release readiness summaries, and audit-ready documentation.
Collaborate with globally distributed teams and influence quality outcomes across the SDLC through automation-first thinking, risk-based testing, engineering rigor, and continuous improvement.