Our Company: 

At Teradata, we believe that people thrive when empowered with better information. That’s why we built the most complete cloud analytics and data platform for AI. By delivering harmonized data, trusted AI, and faster innovation, we uplift and empower our customers—and our customers’ customers—to make better, more confident decisions. The world’s top companies across every major industry trust Teradata to improve business performance, enrich customer experiences, and fully integrate data across the enterprise. 

What you will do: 

In this role you will lead a critical and highly visible function within Teradata Vantage platform. You will be given the opportunity to autonomously deliver the technical direction of the service, and the feature roadmap. You will work with extraordinary talent and have the opportunity to shape the team to best execute on the product. 

Job Responsibilities: 

• Design, implement, test, deploy, and maintain Python-based SDKs and libraries that integrate with the Teradata Vantage platform and related AI ecosystems.
• Build high-quality, modular, and reusable Python packages that expose APIs and connectors for internal and external use.
• Collaborate with AI and platform teams to integrate LLM and agentic capabilities (e.g., LangChain, LangGraph, or Model Context Protocol integrations) into existing Python packages.
• Ensure seamless interoperability between the Python packages and cloud-native services (AWS, GCP, Azure) and Teradata components.
• Develop tools, utilities, and abstractions to simplify data access, orchestration, and intelligent context sharing across applications.
• Write comprehensive unit and integration tests, participate in peer code reviews, and ensure adherence to coding best practices.
• Troubleshoot issues, optimize performance, and contribute to the design of scalable, maintainable distributed systems.
• Collaborate closely with cross-functional teams — AI engineers, data scientists, and platform engineers — in an Agile, fast-paced environment.
• Document design, API interfaces, and usage examples to enable broad adoption and developer productivity.
• Support the deployment of agent systems in scalable environments using Kubernetes, Docker, and cloud services (AWS, Azure, or GCP).

What makes you a qualified candidate: 

• 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++.
• Familiarity with MCP, OpenAI, Hugging Face, Claude, LangChain, VectorDatabase is a plus.
• Basic understanding of how to use AI tools 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.

What you will bring: 

• BS degree in Computer Science, Artificial Intelligence, Software Engineering, or related technical field.
• Strong problem-solving skills and a solid foundation in data structures, algorithms, and object-oriented programming.
• Experience with cloud tools and platforms (AWS, GCP, Azure), especially Kubernetes and Docker.
• Exposure to agentic frameworks such as LangChain, AutoGen, CrewAI, or similar tools is a plus.
• Hands-on experience or familiarity with Model Context Protocol (MCP) for agent context management is a plus.
• Hands-on experience or working knowledge of cloud-native deployment and orchestration on CSP platforms.
• Curiosity and excitement about building intelligent systems that act autonomously and adaptively.
• A mindset geared toward experimentation, continuous learning, and pushing the boundaries of AI capabilities.

#LI-AN1