Teradata is looking to solve the problem of unleashing the full potential of data by empowering the world's largest enterprises to derive unprecedented value from their most complex data using Artificial Intelligence, especially in the realm of autonomous and agentic systems
Requirements
- Experience working with modern data platforms like Teradata, Snowflake, and Databricks
- Hands-on experience with Machine learning & deep learning frameworks : TensorFlow, PyTorch, Scikit-learn
- Hands-on experience with LLMs , agent frameworks (LangChain, AutoGPT, ReAct, etc.), and orchestration tools
- Strong engineering background (Python/Java/Golang, API integration, backend frameworks)
- Strong system design skills and understanding of distributed systems
- Experience with AI observability tools and practices (e.g., logging, monitoring, tracing, metrics for AI agents or ML models)
- Familiarity with containerized environments ( Docker , Kubernetes ) and CI/CD pipelines
Responsibilities
- Design, develop, and deploy agentic systems integrated into the data platform
- Build dashboards and metrics pipelines to track key AI system indicators: latency, accuracy, tool invocation success, hallucination rate, and failure modes
- Integrate observability tooling (e.g., OpenTelemetry, Prometheus, Grafana) with LLM-based workflows and agent pipelines
- Work alongside a high-caliber team of AI researchers, engineers, and data scientists tackling some of the hardest problems in AI and enterprise software
- Develop and deploy advanced AI agents that integrate deeply with business operations, turning data into insight, action, and measurable outcomes
- Ensure AI systems behave deterministically when needed and are reliable, debuggable, and observable
- Collaborate daily with some of the brightest minds in the company to deliver high-quality, critical, and highly visible AI/ML functionality within the Teradata Vantage platform
Other
- A Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field
- 3+ years of experience in software architecture, backend systems, or AI infrastructure
- Passion for building safe, human-aligned autonomous systems
- Genuine excitement for AI and large language models (LLMs) is a significant advantage
- Strong knowledge of LLMs, RL, or cognitive architectures is highly desirable
