Senior Artificial Intelligence Engineer

• 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 AWS, Azure, or GCP, with best-in-class observability and fault tolerance.
• 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.
• 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.

• 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.
• Familiarity with vector databases (Pinecone, Weaviate, FAISS) and embedding models for semantic search and retrieval-augmented generation (RAG).
• Deep experience working with cloud platforms (AWS, Azure, or GCP), containerized environments (Docker/Kubernetes), and infrastructure-as-code (Terraform, Ansible).
• 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.

Teradata