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Hansen

DevOps Engineer

Hansen Carlsbad, California, United States

Software Development · 1,001-5,000 employees

6 h ago
devops Mid (2-5 yrs) Full-time United States
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About the role

The DevOps Engineer will design and manage CI/CD pipelines to support the deployment, scaling, and monitoring of autonomous agentic AI systems. They will collaborate with AI engineers to automate cloud infrastructure and ensure secure, reliable operations across hybrid platforms.

What they look for

DevOps CI/CD GitHub Actions Docker Kubernetes Terraform Infrastructure as Code Dynatrace LangChain LangGraph Vector Databases OpenAI APIs n8n Cloud Infrastructure MLOps Security

Requirements

Candidates must have at least 4 years of experience in DevOps, MLOps, or infrastructure engineering with a strong background in automation. Proficiency in containerization, infrastructure as code, and familiarity with AI agent frameworks like LangChain is required.

Full description

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.

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