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Ця вакансія не має повного перекладу вибраною мовою. Нижче показано оригінальний зміст.

Senior AI Engineer, Agentic Systems

Повна зайнятість Дистанційна робота

Дата публікації: 06.08.2026

In this role you will build the agentic systems that power Teradata's next generation of AI-driven analytics — intelligent agents that reason over enterprise data, invoke Vantage capabilities as tools, and complete multi-step analytical tasks autonomously. You will design and implement agent skills and plugins that extend the Teradata agent harness, build evaluation frameworks to measure agent quality, and contribute to the reliability and performance of agent workflows running on Vantage. Your work directly enables customers to move from asking Teradata questions to delegating analytical tasks to AI agents.

Responsibilities

Build the agentic systems that power Teradata's next generation of AI-driven analytics.; Design and implement agent skills and plugins that extend the Teradata agent harness.; Build evaluation frameworks to measure agent quality.; Contribute to the reliability and performance of agent workflows running on Vantage.; Enable customers to move from asking Teradata questions to delegating analytical tasks to AI agents.

Requirements

3–6 years of software engineering experience with at least 2 years building agentic AI systems in production — not just RAG pipelines or chatbots.; Hands-on experience implementing agent skills, plugins, or tools that extend an agent harness (Claude Code, OpenCode, Codex, OpenClaw, LangGraph, or equivalent).; Proficiency in Python.; Understanding of agent planning loops, tool-calling protocols, function calling APIs (OpenAI, Anthropic, or Google format), and prompt engineering for reliability.

Nice to have

Go experience.; Open-source contributions to agent frameworks or LLM tooling.; Experience evaluating and benchmarking agentic systems (building evals, golden datasets, and automated regression testing for agent behaviors).; Familiarity with Teradata Vantage, SQL query optimization, or columnar analytics, or with a competing platform (Snowflake, Databricks, BigQuery) at depth.; Experience with vector databases, embedding models, and hybrid retrieval for agent memory and context management.; Strong written communication.; A passion for how AI can unlock potential to help teams, customers, and communities achieve great things.

Benefits

Healthcare; Life and disability insurance; Retirement savings; Time-off programs; 401(k)-retirement savings plan; Annual incentive plans; Flexible work model; People-first culture; Focus on well-being; Anti-racist company; Diversity, Equity, and Inclusion commitment.
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