Network Automation Engineer

Realm; Austin (TX); On-site; USD 100,000 - 130,000; Full time

Job summary

A technology company seeking an experienced engineer to lead automation initiatives across data center networks supporting AI-driven workloads. The role requires strong programming skills in Python or Go, with a focus on network engineering and automation. Responsibilities include designing data representations, developing deployment tools, and implementing automated workflows. Ideal candidates have a minimum of five years in network engineering, with experience in DCIM systems and configuration frameworks. Competitive salary offered.

Qualifications

• Strong programming capability in Python or Go, with production-grade automation experience.
• At least five years of professional experience in network engineering with a focus on automation.
• Hands-on experience with configuration templating and network automation frameworks.

Responsibilities

• Design structured network data representations within DCIM/IPAM platforms.
• Develop tooling that produces deployment artifacts directly from modeled network intent.
• Implement automated provisioning workflows including zero-touch device onboarding.

Skills

Python programming

Go programming

Network automation

API integrations

Infrastructure-as-code

Data center networking

Job description

An experienced engineer is sought to lead automation initiatives across large-scale data center network environments supporting high-density compute and AI-driven workloads.

This position combines software engineering and advanced networking expertise, with responsibility for eliminating manual processes and establishing model-driven, repeatable infrastructure deployment systems.

Core Responsibilities

• Design structured network data representations within DCIM/IPAM platforms to serve as the authoritative source for automation systems
• Develop tooling that produces deployment artifacts (rack layouts, cabling documentation, port allocation matrices) directly from modeled network intent
• Build configuration rendering pipelines that transform structured data into production-ready device configurations
• Implement automated provisioning workflows, including zero-touch device onboarding and bootstrap processes
• Create validation and health-check frameworks to verify infrastructure readiness prior to workload activation
• Develop mechanisms to detect configuration drift and deployment inconsistencies
• Partner with software, deployment, and infrastructure teams to ensure consistency between physical installations and logical network design
• Contribute to architectural decisions that improve scalability, determinism, and operational reliability across the automation stack

The objective is to make network deployments deterministic, reproducible, and scalable across multiple data center builds.

Required Experience

• Strong programming capability in Python or Go, with production-grade automation experience
• At least five years of professional experience in network engineering, with significant emphasis on automation and tooling
• Practical experience working with DCIM and/or IPAM systems, including API integrations and structured data modeling
• Hands‑on experience with configuration templating and network automation frameworks
• Familiarity with infrastructure‑as‑code concepts and reproducible provisioning methodologies
• Experience operating and configuring modern data center switching platforms and network operating systems
• Ability to document architectural decisions and communicate complex technical concepts clearly

Preferred Qualifications

• Experience generating deployment documentation programmatically from network models
• Familiarity with zero‑touch provisioning systems and device bootstrap automation
• Strong understanding of routing protocols, overlay networking, and core data center networking concepts
• Experience developing automated validation or testing frameworks for network infrastructure
• Exposure to GPU cluster networking, AI infrastructure, or high‑performance computing environments
• Knowledge of monitoring and observability systems integrated with automation workflows
• Understanding of container networking models and orchestration platforms
• Experience using virtual lab or simulation environments for pre‑production network testing