Principal Platform Engineer, AI – Automation

Jobtailor

Phoenix (AZ)

On-site

USD 170,000 - 210,000

Full time

14 days+

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Job summary

Jobtailor in Phoenix, AZ seeks a senior software engineer to drive automation across Global Host Platform systems and build scalable internal tools for global scale. You will leverage Python, Bash, Terraform, Ansible, Docker and Kubernetes, lead deep dives, mentor engineers, and champion AI tooling to accelerate reliability and throughput.

The role requires 8+ years of hands-on software engineering, strong scripting and IaC skills, and experience with agentic AI in production.

Qualifications

8+ years of hands-on software engineering experience; systems or backend engineering preferred.
Hands-on experience with AI developer tools (Claude Code, GitHub Copilot, Cursor, etc.), LLM-backed scripting, and agentic AI systems capable of planning, tool use, and autonomous task execution in engineering workflows.
Agentic AI in both our developer processes and production services is a must — you build with it day-to-day and you run it where reliability actually counts.
Strong command of multiple scripting languages and infrastructure-as-code tooling.
Experience with automated VM deployments (VMware) and automated configuration management (Ansible).
Containerizing software and tools (Docker, Podman) and deploying them in orchestrated environments (Kubernetes).
Experience in SRE, DevOps, or platform engineering — or the curiosity and track record to ramp up fast.
A genuine drive to reduce tech debt, enable teammates, and automate the annoying stuff.
Ability to lead a team in blending software engineering best practices with fast-moving AI capabilities — and to keep that blend current as both continue to evolve.
A habit of keeping pace with a market that moves weekly, not yearly — and the instinct to lead and teach others so the whole team stays current, not just you.
Excellent communication and collaboration skills; you enjoy being a multiplier.
Nice to have: Background in high-scale production systems (AWS, observability platforms, etc.).
Nice to have: Experience building or operating MCP servers, or integrating AI agents with internal tooling.
Nice to have: Experience introducing new development practices or tooling into an existing engineering org.
Nice to have: Prior involvement in incident management, disaster recovery, or reliability strategy.

Responsibilities

Write high-quality, maintainable code to accelerate platform automation and reduce tech debt.
Build internal tools to keep systems scalable and resilient at global scale under peak load.
Use Python, Bash and Terraform/Ansible to simplify operational workflows.
Lead deep-dives to spot automation opportunities and tackle inefficiencies.
Drive adoption of AI developer tools across the team.
Design agentic AI workflows for autonomous task execution and tool chaining.
Define patterns for LLM-backed development and AI-augmented refactoring.
Set internal standards for platform automation, SRE, and code quality.
Mentor engineers and spread knowledge on AI tooling.
Partner with reliability engineers to deliver durable automation.
Lead in-person trainings, gatherings, and hackathons on-site monthly, travel quarterly.

Skills

Python Scripting

Leadership

Mentoring

Excellent Communication

Team Building

AI Developer Tools

Tools

Terraform

Ansible

Docker

Podman

Kubernetes

AWS

VMware

Job description

Write high-quality, maintainable code that accelerates platform automation and reduces tech debt across Global Host Platform systems.
Build the internal tools that keep our systems scalable and resilient at global scale — engineered to hold up under the peak load of high-demand onsales.
Use scripting (Python, Bash) and infrastructure-as-code (Terraform, Ansible) to simplify and standardize operational workflows.
Lead technical deep-dives to spot automation opportunities and tackle long-standing inefficiencies.
Drive adoption of AI developer tools — e.g. Claude Code, GitHub Copilot, Cursor, Amazon Q, and local models via Ollama — across the team.
Design and champion agentic AI workflows that plan, reason, and act — building frameworks for autonomous task execution and tool chaining, including via the Model Context Protocol (MCP).
Define and evolve our internal patterns for LLM-backed development, spec-driven workflows, and AI-augmented refactoring — with attention to code quality, security, and human review.
Define and evangelize internal standards for platform automation, SRE practice, and code quality.
Mentor engineers and spread knowledge across the team, especially on getting real leverage from modern AI tooling.
Partner with reliability and platform engineers to deliver automation that sticks — measurable impact over buzzwords.
Lead in-person team trainings, gatherings, and hackathons on-site monthly, and travel quarterly.

Requirements

8+ years of hands-on software engineering experience; systems or backend engineering preferred.
Hands-on experience with AI developer tools (Claude Code, GitHub Copilot, Cursor, etc.), LLM-backed scripting, and agentic AI systems capable of planning, tool use, and autonomous task execution in engineering workflows.
Agentic AI in both our developer processes and our production services is a must — you build with it day-to-day and you run it where reliability actually counts.
Strong command of multiple scripting languages and infrastructure-as-code tooling.
Experience with automated VM deployments (VMware) and automated configuration management (Ansible).
Containerizing software and tools (Docker, Podman) and deploying them in orchestrated environments (Kubernetes).
Experience in SRE, DevOps, or platform engineering — or the curiosity and track record to ramp up fast.
A genuine drive to reduce tech debt, enable teammates, and automate the annoying stuff.
Ability to lead a team in blending software engineering best practices with fast-moving AI capabilities — and to keep that blend current as both continue to evolve.
A habit of keeping pace with a market that moves weekly, not yearly — and the instinct to lead and teach others so the whole team stays current, not just you.
Excellent communication and collaboration skills; you enjoy being a multiplier.
Nice to have: Background in high-scale production systems (AWS, observability platforms, etc.).
Nice to have: Experience building or operating MCP servers, or integrating AI agents with internal tooling.
Nice to have: Experience introducing new development practices or tooling into an existing engineering org.
Nice to have: Prior involvement in incident management, disaster recovery, or reliability strategy.

Core Competencies

Demonstrates expertise in software engineering with a focus on automation, AI developer tools, and infrastructure-as-code practices. Proven ability to mentor teams, drive adoption of modern technologies, and enhance operational workflows for scalable and resilient systems.

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