DevOps Engineer

Hansen Technologies; Carlsbad (CA); On-site; USD 140,000 - 200,000; Full time

Job summary

Hansen Technologies in Carlsbad, CA is seeking a DevOps Engineer to own the deployment, scaling, and monitoring of GenAI systems across cloud-native and hybrid platforms. You will collaborate with AI Engineers and infrastructure teams to ensure reliable and secure AI operations.

Responsibilities include building robust CI/CD pipelines, automating cloud infrastructure, and implementing comprehensive observability with Dynatrace.

Qualifications

• 4+ years in DevOps, MLOps, or infrastructure engineering.
• Automation and infrastructure management for AI workloads.
• Containerization with Docker/Kubernetes, and IaC with Terraform.
• Experience with GitHub Actions and hybrid cloud deployments.
• Familiarity with Dynatrace for production monitoring.
• Experience with LangChain, LangGraph, and vector DBs.
• Strong security, scripting, and CI/CD automation.
• Collaborative and proactive in reliable, scalable AI systems.

Responsibilities

• Design and manage CI/CD pipelines using GitHub.
• Build and automate cloud infra for autonomous AI agents.
• Implement monitoring, logging, and alerting for AI processes.
• Collaborate with AI engineers to streamline training and deployment.
• Ensure security, access control, and compliance for AI data.
• Containerize and deploy LLM apps on hybrid infra.
• Configure Dynatrace for observability and incident response.
• Automate workflows with n8n.
• Secure AI pipelines and manage secrets.
• Support QA integration with test automation tools such as Functionize, Mabl, and Port.

Skills

DevOps

MLOps

Automation

Security

Collaboration

Tools

Docker

Kubernetes

Terraform

GitHub Actions

Dynatrace

n8n

LangChain

LangGraph

Qdrant

Job description

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.

Job Description

Location

Carlsbad, CA United States (Onsite)

Type

Full-time

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.