Our Company:
At Teradata, we believe that people thrive when empowered with better information. Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI.
What You'll Do
We are seeking a highly experienced Senior AI Engineer to lead the design and development of AI agents, skills, and internal tools that materially accelerate test development, automation, execution, and analysis. This role sits at the intersection of quality engineering, internal tooling, and applied AI, and will help scale AI adoption across test and quality teams while contributing reusable agent capabilities for broader engineering teams.
You will own end‑to‑end delivery of AI‑powered solutions - from problem discovery and technical design through production implementation, measurement, and iteration - while partnering closely with quality engineers, platform teams, and architects.
Key Responsibilities
1) AI Agents & Skills for Test and Quality Engineering
- Design and deliver agentic solutions that help engineers and SDETs:
- Generate, refine, and maintain test cases and test assets
- Automate repetitive testing workflows
- Summarize failures and recommend likely causes using logs, traces, and run artifacts
- Improve feedback loops through intelligent prioritization and actionable insights
- Build and evolve AI capabilities that enhance test coverage, selection, and execution efficiency, including intelligent test optimization use cases .
2) AI‑Powered Test Automation Frameworks & Pipelines
- Architect and implement AI‑powered test automation frameworks and tooling that are scalable and resilient .
- Develop self‑healing/adaptive automation approaches that reduce maintenance overhead as UI/API/data layers evolve .
- Integrate intelligent testing into CI/CD pipelines and engineering workflows in partnership with DevOps/Platform teams .
3) Quality Signals, Analytics & Continuous Improvement
- Analyze test run data and quality signals to identify patterns, anomalies, and improvement opportunities, and translate them into tooling/agent enhancements .
- Build automated workflows for complex validation scenarios (e.g., integration/system validation, data integrity checks) where applicable to your ecosystem .
4) Technical Leadership & Enablement
- Provide technical direction, code reviews, and mentorship to engineers contributing to AI‑assisted testing initiatives .
- Evaluate and integrate third‑party AI testing tools and platforms where they accelerate outcomes, with attention to maintainability and fit .
- Contribute to evolving standards and best practices for AI‑assisted test development and automation .
Who You’ll Work With
- Quality engineering (SDETs/QA), internal engineering tooling, and architecture partners
- AI‑assisted testing frameworks and automation pipelines
- Cross‑team internal users adopting AI‑enabled engineering practices (test and beyond)
What Makes You a Qualified Candidate
- Bachelor’s/Master’s in Computer Science or equivalent.
- 5+ years experience in software engineering and/or test automation (including building frameworks/tools used by other engineers).
- Strong proficiency in Python and Linux/Unix environments .
- Demonstrated applied experience using AI/ML and/or generative AI to improve engineering workflows (testing, automation, developer productivity).
- Proven track record integrating automation into CI/CD pipelines and delivering maintainable systems adopted by teams .
- Strong problem solving, design skills, and ability to deliver across ambiguous problem spaces.
What You'll Bring
- Hands‑on experience building AI agents (planning/tool use, retrieval, evaluation) for internal engineering.
- Experience with Docker and modern test execution environments; Kubernetes is a plus .
- Experience with test intelligence use cases such as defect prediction, test selection optimization, or coverage insights .
- Experience establishing team practices around AI solution quality, safety, and operational readiness.
#LI-TC1
