This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
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 Responsibility
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
Requirements
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
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