Job Description

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, develop, and scale intelligent software systems that power autonomous AI agents capable of reasoning, planning, acting, and learning in real-world environments.



Lead the implementation of core Agentic AI components -- including agent memory, context-aware planning, multi-step tool use, and self-reflective behavior loops.



Architect robust, cloud-native backends that support high-throughput agent pipelines across major Cloud Service Providers (AWS, Azure, GCP), ensuring best-in-class observability, fault tolerance, and scalability.



Build seamless integrations with large language models (LLMs) such as GPT-4, Claude, Gemini, or open-source models -- using advanced techniques like function calling, dynamic prompting, and multi-agent orchestration.



Design and implement standardized context management and sharing using the Model Context Protocol (MCP) to enable consistent, interoperable agent and tool interactions.



Develop scalable APIs and services to connect agents with internal tools, vector databases, RAG pipelines, and external APIs.



Own technical delivery of major agent-related features, leading design reviews, code quality standards, and engineering best practices.



Collaborate cross-functionally with researchers, ML engineers, product managers, and UX teams to translate ideas into intelligent, performant, and production-ready systems.



Define and implement testing strategies to validate agentic behavior in both deterministic and probabilistic conditions.



Guide junior engineers and peers by mentoring, unblocking challenges, and championing a culture of technical excellence.



Continuously evaluate emerging frameworks, libraries, and research to drive innovation in our Agentic AI stack.

What makes you a qualified candidate:

5+ years of hands-on experience in backend development, distributed systems, or AI infrastructure, with a proven track record of delivering in high-scale environments.



Expertise in building and deploying AI-integrated software, particularly with LLMs and frameworks like LangChain, AutoGen, CrewAI, Semantic Kernel, or custom orchestrators.



Strong development skills in Python (preferred), Go, Java, or similar languages used in intelligent system design.



Practical knowledge of agentic AI principles -- including task decomposition, autonomous decision-making, memory/context management, and multi-agent collaboration.



Experience implementing or integrating the Model Context Protocol (MCP) to facilitate standardized agent context management and interoperability across tools.



Extensive experience with Cloud Service Providers (AWS, Azure, GCP) including cloud-native infrastructure, container orchestration (Docker, Kubernetes), and infrastructure-as-code tools (Terraform, Ansible).



Familiarity with vector databases (Pinecone, Weaviate, FAISS) and embedding models for semantic search and retrieval-augmented generation (RAG).



Demonstrated ability to design clean APIs, modular microservices, and resilient, maintainable backend systems.



Clear communicator with the ability to simplify complex AI system behaviors into actionable architecture.



Passion for AI and a hunger to build systems that push the boundaries of autonomous software.



Strong understanding of Agile software development, CI/CD practices, and collaborative team workflows.

What you will bring:

BS or MS degree in Computer Science, Artificial Intelligence, Software Engineering, or a related technical field.



A solid foundation in software engineering principles, including system design, data structures, algorithms, and distributed computing.



Proven ability to work in a fast-paced, innovation-driven environment where engineers take full ownership from concept to deployment.



Experience deploying and operating intelligent systems in production environments with live users and evolving requirements.



Curiosity, creativity, and the mindset of a builder -- someone who thrives at the intersection of AI research and real-world impact.



Desire to help shape the future of software agents by building scalable, reliable, and intelligent backends that unlock new capabilities in autonomy and adaptability.



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