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.
Your work will directly shape how Teradata builds, monitors, and operates its AI-powered platform. Success in this role means measurable improvements in engineering efficiency, system reliability, and autonomous operations maturity.
Who You'll Work With
Build the AI Platform tooling, automation, and agentic frameworks that power next-generation applications and operational intelligence at Teradata.
You will 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.
This team plays a foundational role in advancing Teradata’s AI-first strategy by transforming how software is built and operated.
What Makes You a Qualified Candidate
12+ 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.
What You'll Bring
Experience building agentic systems for observability, automated remediation, or intelligent diagnostics (ideal background from AI-native or data observability companies such as Acceldata).
Familiarity with OpenTelemetry, Prometheus, distributed tracing systems, or similar observability stacks.
Hands-on experience integrating LLMs into production workflows with proper guardrails and evaluation mechanisms.
Strong understanding of AI-assisted development tooling and productivity optimization.
Experience designing multi-step reasoning workflows and autonomous decision agents.
A systems-thinking mindset that connects AI models, data pipelines, and operational workflows end-to-end.
Strong communication skills with the ability to influence senior engineers and product leaders.
A passion for how AI can unlock potential to help our teams, our customers, and our communities achieve great things.
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