Note: The job is a remote job and is open to candidates in USA. Teradata is an enterprise intelligence and AI platform company that unifies data, knowledge, and business context to help organizations achieve business outcomes. The Principal Engineer will lead the design and development of AI-native agentic workflows, intelligent observability systems, and autonomous operational tooling across Teradata’s AI Platform. The role focuses on building AI agents that improve engineering productivity, system reliability, debugging, and operational efficiency.
Responsibilities
- 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
- This is a Senior Individual Contributor role focused on building and deploying intelligent agents—not just integrating automation tools, but architecting AI-driven systems that reason, analyze, and act across telemetry, applications, and workflows
- 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
- 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
Skills
- 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
- 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
Benefits
- A flexible work model, with flexibility about how, when, and where you work
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