Teradata is focused on unleashing the full potential of data through its ClearScape Analytics™ platform. As an AI Fullstack Software Engineer Intern, you will work on designing and deploying advanced AI agents that integrate with business operations, collaborating with a team of AI researchers and engineers to solve complex problems in AI and enterprise software.
Responsibilities
Experience working with modern data platforms like Teradata, Snowflake, and Databricks
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.
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.
Strong engineering background (Python/Java/Golang, API integration, backend frameworks)
Strong system design skills and understanding of distributed systems.
You’re obsessive about reliability, debuggability, and ensuring AI systems behave deterministically when needed.
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).
Solid understanding of model performance monitoring, drift detection, and responsible AI principles.
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.
Qualification
Required
Experience working with modern data platforms like Teradata, Snowflake, and Databricks
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.
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.
Strong engineering background (Python/Java/Golang, API integration, backend frameworks)
Strong system design skills and understanding of distributed systems.
You’re obsessive about reliability, debuggability, and ensuring AI systems behave deterministically when needed.
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).
Solid understanding of model performance monitoring, drift detection, and responsible AI principles.
A Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field – your academic foundation is key.
A genuine excitement for AI and large language models (LLMs) is a significant advantage – you'll be working at the cutting edge!
UI/UX Development: Proficiency in JavaScript frameworks (React. js, Vue. js, Angular) and CSS libraries (Bootstrap, Material-UI).
Design, develop, and deploy agentic systems integrated into the data platform.
3+ years of experience in software architecture, backend systems, or AI infrastructure.
Strong knowledge of LLMs, RL, or cognitive architectures is highly desirable.
Passion for building safe, human-aligned autonomous systems.
Experience in software development (Python, Go, or Java preferred).
Familiarity with backend service development, APIs, and distributed systems.
Interest or experience in LLMs, autonomous agents, or AI tooling.
Familiarity with containerized environments (Docker, Kubernetes) and CI/CD pipelines.
Experience with AI observability tools and practices (e. g. , logging, monitoring, tracing, metrics for AI agents or ML models).
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.
You're knowledgeable about open-source tools and technologies and know how to leverage and extend them to build innovative solutions.
Preferred
Bonus: Research experience or contributions to open-source agentic frameworks.
Benefits
Flexible work model
Well-being focus
People-first culture
Commitment to Diversity, Equity, and Inclusion
Teradata is the connected multi-cloud data platform company. Our enterprise analytics solve business challenges from start to scale.
