Teradata is looking to solve complex AI and enterprise software problems by building intelligent systems that go beyond automation, enabling them to observe, reason, adapt, and drive complex decision-making across large-scale enterprise environments. They aim to integrate advanced AI agents deeply with business operations to transform data into insight, action, and measurable outcomes, pushing the boundaries of AI, especially in autonomous and agentic systems.
Requirements
- Experience working with modern data platforms like Teradata, Snowflake, and Databricks
- Strong engineering background (Python/Java/Golang, API integration, backend frameworks)
- Strong system design skills and understanding of distributed systems.
- 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.
- 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 intuitive UI with user-friendly natural language interfaces (e.g., chatbots, AI assistants) to allow users to interact with the data platform using natural language queries.
- 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.
- Design and deploy advanced AI agents that integrate deeply with business operations.
- Develop scalable multi-agent coordination and fine-tuned LLM applications.
- Implement real-time monitoring, drift detection, and closed-loop retraining systems.
Other
- A Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field
- Passion for staying current with AI research, especially in the areas of reasoning, planning, and autonomous systems.
- You are an excellent full stack engineer who codes daily and owns systems end-to-end.
- You’re obsessive about reliability, debuggability, and ensuring AI systems behave deterministically when needed.
- Solid understanding of model performance monitoring , drift detection, and responsible AI principles.
