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

• Drive quality transformation by reimagining system and integration testing using a strong customer-centric, outside-in perspective, ensuring alignment with real-world scenarios.
• Leverage AI-enabled testing approaches to accelerate productivity and automation, including adoption of:
  • LLM-based test generation
  • AI copilots and agents
  • Intelligent failure analysis and test optimization
• Lead system and integration validation at scale, ensuring robust coverage across distributed systems, cloud environments, and complex enterprise workflows.
• Enable continuous validation and faster releases by embedding automation-first practices into CI/CD pipelines and adopting data-driven, adaptive testing techniques.
• Improve engineering productivity and quality signals by reducing manual effort, enhancing test efficiency, and enabling actionable insights from test results.
• Provide strong technical leadership (IC role) by influencing architecture, mentoring teams, and driving adoption of modern, AI-driven quality engineering practices.

 What You’ll Bring

• Bachelor’s or Master’s degree in Computer Science or related field
• 10+ years of experience in software engineering with deep focus on testing, system validation, and quality engineering
• Strong core experience in system and integration testing for large-scale enterprise platforms, with a proven track record in driving quality strategy and validation at scale
• Hands-on expertise with AI-enabled tools to accelerate engineering productivity, including:
  • LLM-based test generation
  • AI copilots and intelligent failure analysis
  • Test intelligence and optimization platforms
• Demonstrated ability to deliver measurable impact (reduced manual effort, faster turnaround, improved automation effectiveness)
• Deep automation and system expertise, including:
  • Automation across system, API, and integration layers
  • CI/CD and continuous validation practices
  • Distributed systems and cloud environments
• Strong technical leadership and influence as an IC, with ability to drive cross-team adoption, collaborate effectively, and champion AI-driven quality engineering innovation

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