Apply for the latest AI Engineer job opening at Terradata in 2026. Terradata is currently hiring Experienced professionals for this Hyderabad role. This is a great opportunity to join Terradata. Don't miss this chance — apply as soon as possible!
About Terradata
At Teradata, we believe that people thrive when empowered with trusted information. Our best-in-class cloud analytics and data platform delivers harmonized data, trusted AI/ML, and faster innovation for better decision-making.
For billions of people around the globe, Teradata is improving everyday lives by managing trillions of digital interactions — each one a data point to better inform or an insight to empower more confident decisions.
Businesses use Teradata to deliver rapid innovation, scale operational efficiency, reduce friction in supply chains, and protect the enterprise’s most valuable information — all with the goal of creating better customer experiences and growing organizations from start to scale.
1–3 years of experience (or strong academic/internship background) in software development with a focus on AI/ML, intelligent systems, or cloud-native applications.
Strong interest in Agentic AI — systems where AI agents can autonomously interpret goals, take actions, and learn from outcomes.
Familiarity with one or more programming languages: Python (preferred), Go, Java, or C++.
Exposure to LLMs and AI APIs (e.g., OpenAI, Hugging Face, Claude) and understanding of prompting, embeddings, or vector databases.
Basic understanding of how AI agents use tools and memory to solve complex tasks.
Experience with RESTful APIs, backend service design, and microservice architectures.
Familiarity with modern cloud infrastructure (AWS, GCP, or Azure), especially in deploying containerized applications.
Ability to write clean, testable code and follow best practices in code reviews and version control.
Clear communicator, with a willingness to ask questions, propose ideas, and collaborate across teams.
Passion for learning emerging AI techniques and contributing to real-world agentic applications.
Key Responsibilities
Contribute to the design and development of software components that enable autonomous AI agents to reason, plan, act, and learn.
Implement features that support agentic capabilities such as tool use, memory, long-term planning, task execution, and self-reflection.
Integrate with state-of-the-art LLMs (e.g., OpenAI, Anthropic) and agent orchestration frameworks (e.g., LangChain, CrewAI, AutoGen).
Write, test, and debug Python or other backend code that powers agent workflows in cloud-native environments.
Assist in building interfaces between agents and tools such as APIs, databases, search engines, and user-facing applications.
Participate in Agile development workflows — sprint planning, code reviews, retrospectives — and collaborate across AI, product, and engineering teams.
Work with structured and unstructured data to support context-aware reasoning and decision-making in agents.
Contribute to the development of internal testing tools and evaluation methods for autonomous agent behaviors.
Support the deployment of agent systems in scalable environments using Kubernetes, Docker, and cloud services (AWS, Azure, or GCP).
Maintain documentation of agent capabilities, system design, and integration strategies.
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