01Key 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 .
