Senior AI DevOps / LLMOps

Key details

• Automate Build-to-Production processes
• Design and implement robust CI/CD pipelines tailored for AI, covering model weights, dataset versioning, and application code
• Develop specialized workflows for PromptOps, ensuring system prompts are version-controlled, tested for regressions, and deployed with the same rigor as traditional code
• Automate the deployment of Agentic workflows, managing stateful AI interactions and multi-agent handoffs
• Provision and manage high-performance compute environments (GPU clusters, TPU pods) using Terraform, Pulumi, or Ansible
• Define and enforce Policy-as-Code for AI endpoints to ensure compliance with security, cost-usage limits, and data residency requirements
• Maintain a consistent environment across Hybrid Infrastructure, ensuring seamless parity between On-Premises development and Cloud production
• Architect Progressive Delivery strategies for AI, including Canary releases, Blue-Green deployments, and Shadowing
• Build Evaluation-in-the-Loop gates within the pipeline to automatically test for bias, hallucination, and performance degradation before a release
• Implement A/B testing frameworks specifically designed for LLM outputs and agentic behavior
• Establish deep observability into Inference Endpoints, tracking metrics like tokens-per-second, latency, and drift in model accuracy
• Integrate feedback loops that capture production edge cases to feed back into the training and fine-tuning pipelines
• Company mission
• Information not specified