Location

Carlsbad, CA United States (Onsite)

Type

Full-time

Role Summary

The DevOps Engineer will own the deployment, scaling, and monitoring of GenAI systems across cloud-native and hybrid platforms. You'll collaborate with AI Engineers and infrastructure teams to ensure reliable and secure AI operations.

Key Responsibilities

• Design and manage CI/CD pipelines using GitHub
• Develop and maintain robust CI/CD pipelines tailored specifically for deploying autonomous agentic AI systems and related software components.
• Build and automate cloud infrastructure optimized for deploying, scaling, and managing autonomous AI agents.
• Implement comprehensive monitoring, logging, and alerting for agentic AI processes, ensuring reliability, performance, and continuous improvement.
• Collaborate closely with Agentic AI engineers and architects to streamline workflows for training, deploying, and updating agentic AI models.
• Manage infrastructure security, access control, and compliance related to sensitive AI data and automated agent operations.
• Containerize and deploy LLM apps on hybrid infrastructure (e.g., public cloud, on-prem)
• Configure observability platforms such as Dynatrace for observability and incident response
• Automate integration and event-driven workflows using n8n
• Secure AI pipelines, manage secrets, and enable role-based access controls
• Collaborate with QA for integration with test automation tools such as Functionize, Mabl, and Port

Requirements

• 4+ years in DevOps, MLOps, or infrastructure engineering
• Extensive experience with automation and infrastructure management supporting AI agent workloads.
• Expertise with containerization (Docker, Kubernetes), IaC (Terraform), and orchestration tools for agentic AI platforms.
• Familiarity with platforms and frameworks commonly used for autonomous AI agents (e.g., LangChain, LangGraph, Vector DBs, OpenAI APIs).
• Experience with GitHub Actions, container orchestration, MCP Servers, and hybrid cloud deployment
• Familiarity with Dynatrace for production monitoring
• Experience supporting LangChain, LangGraph, and vector databases (e.g., Qdrant)
• Strong security, scripting, and CI/CD automation background
• Detail-oriented and proactive approach to system reliability, scalability, and security.
• Strong collaboration skills to efficiently support agile development cycles for agentic AI products.