Staff AI Engineer

About the role

**Our Company**

At Teradata, we believe that people thrive when empowered with better information. That’s why we build the most complete cloud analytics and data platform for AI. By delivering harmonized data, trusted AI, and faster innovation, we empower the world’s leading enterprises to make confident, data‑driven decisions at scale.

**The Role**

We're looking for a Staff AI Engineer to lead the architecture and delivery of production\-grade AI agent systems. You will set technical direction, define engineering standards, and work hands\-on across agent design, evaluation, and platform infrastructure while mentoring senior engineers and influencing the broader product roadmap.

**What You'll Do**

**Technical Leadership \& Architecture**

* Own end\-to\-end architecture for AI agent capabilities: agentic workflows, MCP integrations, governance and guardrails, evaluation platforms, and autonomous agent patterns. * Set technical standards for agent orchestration, tool integration, observability, security, and operational excellence — and drive consistency across engineering teams. * Act as the technical escalation point for complex system design, performance, and reliability challenges.

**AI Systems \& Platform Development**

* Design and implement production\-grade AI systems using LLMs, embeddings, vector databases, and agent\-based architectures including secure, reusable APIs and platform services. * Build governance and observability capabilities: guardrails, explainability, suppression controls, cost monitoring, token tracking, and transparency into agent reasoning and tool execution. * Define standards for MCP server integrations, tool discovery, authentication, and secure agent\-tool interactions.

**Quality \& Operational Excellence**

* Build and evolve evaluation frameworks, golden datasets, and benchmarking methodologies to continuously measure agent quality, safety, and reliability. * Lead AI system hardening, regression testing, failure analysis, and production reliability efforts — defining metrics that validate agent accuracy and business outcomes.

**Mentorship \& Org‑Level Impact**

* Mentor Senior and Staff engineers through design reviews, architecture forums, and hands\-on guidance on agent design, NLP techniques, and system tradeoffs. * Partner with product, infrastructure, and data platform teams to translate business needs into scalable AI solutions, and influence roadmap decisions with technical depth and long\-term platform thinking.

**Required Qualifications (Non‑Negotiable)**

* Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience. * **8\+ years** of experience building backend services, distributed systems, or data/AI platforms. * Strong proficiency in Java and Spring Boot with extensive experience building large\-scale distributed APIs, microservices, and cloud\-native backend systems. * Deep understanding of distributed system design, scalability, fault tolerance, and cloud‑native architectures. * Proven experience designing and operating production systems with SQL and NoSQL data stores.

**Preferred / Differentiating Skills**

* Experience with Agent Harness, Agent Skills, and agentic patterns including tool calling, planning loops, memory, self\-reflection, and multi\-step reasoning (LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar). * Hands\-on experience with LLMs, embeddings, vector databases, and MCP integrations. * Experience building evaluation frameworks, AI governance solutions, or production\-grade agent observability platforms. * Familiarity with cloud environments (AWS, Azure, GCP), Kubernetes, Docker, and CI/CD pipelines.

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