Senior AI Platform Engineer (AI)

Location: Hybrid in Alpharetta, Georgia, USA; at least one in-person interview is required, and some travel is expected.

Company

hirify.global provides software solutions for the automotive parts and repair industry, supporting manufacturers, dealers, suppliers, shops, repairers, and service providers.

What you will do

• Design, build, and maintain secure, scalable, highly available cloud platform infrastructure.
• Develop Infrastructure as Code with Terraform, CloudFormation, Ansible, or similar tools.
• Manage AWS, Azure, or Google Cloud environments for reliability, performance, scalability, and cost efficiency.
• Build CI/CD pipelines and improve developer productivity in partnership with software engineering, architecture, and DevOps teams.
• Monitor platform health, troubleshoot production issues, and strengthen security, observability, and operational practices.
• Build platform capabilities for AI-assisted and agentic engineering, including model access, MCP servers and gateways, tool integrations, identity management, governance, auditing, and traceability.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent professional experience.
• 6+ years of experience in software, platform, DevOps, or cloud engineering.
• Strong experience with a major cloud provider, preferably AWS, plus Infrastructure as Code using Terraform, CloudFormation, or similar tools.
• Experience with Docker, Kubernetes, CI/CD pipelines, Linux systems, networking, cloud security, and platform operations.
• Proficiency in Python, Go, Bash, or similar scripting and programming languages, with experience using observability tools such as Datadog, Prometheus, or Grafana.
• Professional experience with AI-assisted development tools and the ability to evaluate AI-generated code and infrastructure for quality, security, and maintainability.

Nice to have

• Experience designing AI platform capabilities and developer tooling.
• Familiarity with LLMs, prompt engineering, agent orchestration, tool or function calling, and Model Context Protocol.
• Understanding of governance, security, and operational requirements for deploying AI agents in production.

Culture & Benefits

• Work in a collaborative environment spanning multiple time zones and international communities.
• Flexibility may include remote, hybrid, or in-person arrangements depending on the role; this position is hybrid.
• Occasional flexibility in work hours may be required for production support, cross-functional initiatives, and collaboration across time zones.
• Opportunities to learn, grow, take risks, and contribute to innovative automotive industry solutions.

Hiring process

• All interviews and technical assessments must be completed personally; proxies or third-party representatives are prohibited.
• Final candidates must participate in at least one in-person interview.