Senior AI Agentic Engineer for Observability & Platform

Teradata Corporation (SE); Honolulu (HI); On-site; USD 217,000 - 326,000; Full time

Benefits offered by this job

Health insurance

401(k) retirement plan

Paid time off

Job summary

Teradata in the United States seeks a Senior Individual Contributor to design and build AI-native agentic workflows that drive engineering productivity, observability, and autonomous operations across the Teradata AI Platform.

You will architect AI agents, integrate LLMs, telemetry, and cloud infrastructure; collaborate with platform and DevOps teams; and apply foundational AI skills to improve efficiency and reliability.

Qualifications

• 8+ years of software engineering experience with AI/ML in production.
• Proven record of building AI agents or autonomous workflows, not just APIs.
• Strong Python (required) and Java or Go programming
• Experience with telemetry data and observability architectures
• Foundational AI skills: prompt engineering, model evaluation, agent orchestration

Responsibilities

• Lead the design and development of AI-native agentic workflows.
• Architect AI agents for observability and automated debugging.
• Design workflows across telemetry pipelines, apps, and cloud infra.
• Develop AI-driven tooling to accelerate development velocity and MTTR.
• Apply LLMs and reasoning frameworks to automate complex diagnostics.
• Drive AI-native development practices across apps and platform engineering.
• Collaborate with engineering teams to embed automation in CI/CD and DevOps.

Skills

Python

Java

Go

Distributed systems

AI/ML systems

Prompt engineering

LLM integration

Observability

Strong communication

Education

Bachelor's degree in related field

Tools

OpenTelemetry

Prometheus

Distributed tracing

Job description

Teradata in the United States seeks a Senior Individual Contributor to design and build AI-native agentic workflows that drive engineering productivity, observability, and autonomous operations across the Teradata AI Platform.

You will architect AI agents, integrate LLMs, telemetry, and cloud infrastructure; collaborate with platform and DevOps teams; and apply foundational AI skills to improve efficiency and reliability.