Principal Engineer, Agentic AI

What You Will Do

• Lead the design and development of AI-native agentic workflows that enhance engineering productivity, observability intelligence, and end-to-end operational excellence across Teradata’s AI Platform.
• Architect and build AI agents for observability, automated root cause analysis, anomaly detection, and engineering productivity optimization.
• Design agentic workflows that integrate across telemetry pipelines, application stacks, and cloud infrastructure.
• Develop AI-driven tooling to accelerate development velocity, reduce operational toil, and improve MTTR.
• Apply LLMs, reasoning frameworks, and advanced AI patterns to automate complex debugging and system diagnostics.
• Drive AI-native development practices across apps, tooling, and platform engineering.
• Partner across engineering teams to embed intelligent automation into CI/CD, DevOps, and support workflows.
• Apply foundational AI skills to explore and implement ways AI can enhance productivity, innovation, and impact across our workforce.

Who You Will Work With

• Build the AI Platform tooling, automation, and agentic frameworks that power next-generation applications and operational intelligence at Teradata.
• Report directly to the VP, AI Apps Tooling & Automation – AI Platform.
• The team drives AI-first application development, intelligent DevOps tooling, and agent-based productivity systems.
• We enable engineering teams across the company to leverage AI responsibly and effectively.
• We partner with AI research, platform engineering, cloud operations, and product teams to integrate observability and automation into the core platform.
• We collaborate with colleagues who share a commitment to leveraging AI responsibly, ensuring our people and customers benefit from the opportunities AI creates.

What Makes You a Qualified Candidate

• 8+ years of experience in software engineering with deep exposure to AI/ML systems in production environments.
• Proven experience building AI agents, LLM-driven systems, or autonomous workflows—not just consuming AI APIs.
• Strong programming expertise in Python (required) and at least one of Java or Go.
• Experience working with distributed systems, telemetry data, and observability architectures.
• Foundational AI skills, including prompt engineering, model evaluation, agent orchestration, reasoning frameworks, and the ability to apply AI to improve engineering and operational outcomes.