Our Company

At Teradata, we believe that people thrive when empowered with better information. Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI.

What You'll Do

At Teradata, we're not just managing data; we're unleashing its full potential. Our Teradata AI Studio platform and pioneering Enterprise Vector Store are empowering the world's largest enterprises to derive unprecedented value from their most complex data. We're rapidly pushing the boundaries of what's possible with Artificial Intelligence, especially in the exciting realm of autonomous and agentic systems

We're building intelligent systems that go far beyond automation — they observe, reason, adapt, and drive complex decision-making across large-scale enterprise environments. As a member of our AI engineering team, you'll play a critical role in designing and deploying advanced AI agents that integrate deeply with business operations, turning data into insight, action, and measurable outcomes.

In this role, you'll architect foundational components for production-grade AI systems — from agent frameworks and LLM pipelines to observability and evaluation layers that ensure reliability, accountability, and performance. You'll be responsible not just for building models, but for making them measurable, debuggable, and trustworthy in real-world, high-stakes deployments.

You'll work alongside a high-caliber team of AI researchers, engineers, and data scientists tackling some of the hardest problems in AI and enterprise software — from scalable multi-agent coordination and fine-tuned LLM applications, to real-time monitoring, drift detection, and closed-loop retraining systems.

If you're passionate about building intelligent systems that are not only powerful but observable, resilient, and production-ready, this role offers the opportunity to shape the future of enterprise AI from the ground up.

Key Responsibilities:

Design and deploy containerized applications using Docker and container orchestration platforms. Understand platform engineering.
Implement and manage Kubernetes clusters for AI/ML workloads, ensuring high availability and scalability.
Build and maintain CI/CD pipelines using Terraform for infrastructure as code and automated deployments.
Collaborate on MLOps practices including model versioning, deployment, and monitoring.
Manage and optimize LLM deployments, including inference endpoints and API gateways.
Design infrastructure to support AI agent orchestration, prompt routing, and multi-agent collaboration.
Implement Kubernetes-native AI microservices to support scalable inference and agent collaboration workloads.
Spearhead the deployment, versioning, and monitoring of ML/LLM models using CI/CD pipelines and MLOps tools.
Automate infrastructure provisioning and configuration using Terraform and Infrastructure as Code principles.
Implement monitoring, logging, and observability solutions for containerized AI/ML applications.
Work with LLM APIs and frameworks to support AI-driven features and integrations.
Collaborate with data science and ML teams to operationalize models into production.
Develop and maintain CI/CD workflows for continuous integration and deployment of ML models.
Ensure system reliability, security, and performance at scale.
Contribute to internal standards and best practices for cloud-native AI system development.
Support containerized application deployments across development, staging, and production environments.

Who You'll Work With

Imagine collaborating daily with some of the brightest minds in the company – individuals who champion diversity, equity, and inclusion as fundamental to our success. You'll be part of a cohesive force, laser-focused on delivering high-quality, critical, and highly visible AI/ML functionality within the Teradata Cloud platform. Your insights will directly shape the future of our intelligent data solutions.

You'll report directly to the inspiring Sr. Manager, Software Engineering, who will champion your growth and empower your contributions.

What Makes You A Qualified Candidate

A Bachelor's or Master's degree in Computer Science, Engineering or a related field – your academic foundation is key.
2+ years of experience in cloud infrastructure, DevOps, or platform engineering.
Experience with cloud platforms (AWS, Azure, or GCP) and cloud-native architectures.
**MUST HAVE**: Strong hands-on experience with containerization technologies (Docker, containerd).
**BIG BONUS**: Experience with Kubernetes (K8s) cluster management and orchestration.
Solid understanding of MLOps principles and practices for ML model lifecycle management.
Knowledge of large language models (LLMs) and experience managing LLM deployments.
Proven experience building and maintaining CI/CD pipelines using Terraform for infrastructure automation.
Proficiency in scripting languages (Python, Bash, or similar) for automation.
Understanding of networking, security, and infrastructure best practices.
Familiarity with monitoring and observability tools (Prometheus, Grafana, ELK stack).
Experience with version control systems (Git) and collaborative development workflows.

What You'll Bring

Experience with Kubernetes ecosystem tools (Helm, Operators, Service Mesh like Istio).
Knowledge of AI/ML frameworks and model serving platforms (TensorFlow Serving, KServe, MLflow).
Experience with LLM-specific tools and frameworks (LangChain, vector databases, prompt engineering).
Familiarity with GitOps practices and tools (ArgoCD, Flux).
Experience with infrastructure security and compliance standards.
Contributions to open-source projects or technical communities.
Strong problem-solving skills and ability to work in a collaborative team environment.
Ownership mindset with a focus on reliability, scalability, and continuous improvement.

Why We Think You'll Love Teradata

We prioritize a people-first culture because we know our people are at the very heart of our success. We embrace a flexible work model because we trust our people to make decisions about how, when, and where they work. We focus on well-being because we care about our people and their ability to thrive both personally and professionally. We are an anti-racist company because our dedication to Diversity, Equity, and Inclusion is more than a statement. It is a deep commitment to doing the work to foster an equitable environment that celebrates people for all of who they are.

Teradata invites all identities and backgrounds in the workplace. We work with deliberation and intent to ensure we are cultivating collaboration and inclusivity across our global organization. We are proud to be an equal opportunity and affirmative action employer. We do not discriminate based upon race, color, ancestry, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related conditions), national origin, sexual orientation, age, citizenship, marital status, disability, medical condition, genetic information, gender identity or expression, military and veteran status, or any other legally protected status.

Senior Cloud AI Engineer - Ai Platform