Senior Fullstack Engineer AI Platform

5 - 9 years

0 Lacs

Posted:1 week ago| Platform: Shine logo

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Job Type

Full Time

Job Description

Role Overview: At Teradata, you will have the opportunity to shape the future of enterprise AI by designing and deploying advanced AI agents that integrate deeply with business operations, turning data into insight, action, and measurable outcomes. You will be part of a high-caliber team working on cutting-edge AI technologies and enterprise software, pushing the boundaries of what's possible with Artificial Intelligence. Key Responsibilities: - Design and prototype interfaces for interacting with autonomous agents - Implement responsive, accessible, and explainable UI components - Partner with AI researchers and software engineers to ensure interfaces support emerging agent capabilities - Conduct usability testing with humans-in-the-loop scenarios - Drive UX best practices for intelligent systems - Experiment with LLM APIs, agentic workflows, and open-source frameworks - Develop and enhance native notebook experiences for seamless interaction with AI workflows - Embrace DevOps practices for rapid iteration and deployment - Implement unit tests for UI components to maintain high-quality user experiences - Strong system design skills and understanding of distributed systems - Ensure reliability, debuggability, and determinism in AI systems Qualifications Required: - Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field - Excitement for AI and large language models (LLMs) - Experience in UI/UX design and frontend engineering - Proficiency in Angular, TypeScript, Figma, and design systems - Knowledge of human-computer interaction, especially with intelligent systems - Familiarity with open-source tools and technologies - Passion for AI/ML and building smart, agent-driven interfaces - Ownership mindset for long-term scalability - Experience in software development (Python, Go, or Java) - Familiarity with containerized environments (Docker, Kubernetes) and CI/CD pipelines - Knowledge of monitoring and scaling ML services on Kubernetes clusters (Note: The additional details of the company were omitted in this summary),

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