Staff Platform Engineer (DevOps)

TL;DR

Staff Platform Engineer (DevOps): Designing and managing scalable cloud infrastructure and DevSecOps capabilities for a cloud-native SaaS platform with an accent on automation, Kubernetes orchestration, and infrastructure-as-code. Focus on implementing zero-downtime strategies, optimizing cost and performance, and mentoring engineering teams to improve developer experience.

Location: Must be based in or able to work from Raleigh-Cary (NC), Austin (TX), Dallas (TX), Tampa (FL), or Boston (MA)

Salary: $145,000–$260,000 USD

Company

hirify.global is a cloud-native SaaS company providing a Context Intelligence Platform that unifies and governs enterprise data to fuel AI-driven decision-making.

What you will do

• Design and manage infrastructure as code (IaC) solutions using Terraform, Crossplane, and Helm.
• Streamline software delivery processes through advanced CI/CD pipelines and automation.
• Monitor, troubleshoot, and optimize cloud infrastructure for cost, reliability, and scalability.
• Develop zero-downtime maintenance strategies for Kubernetes clusters.
• Mentor junior engineers and act as a technical force multiplier across development teams.
• Integrate security controls and AI-driven automation into DevOps workflows.

Requirements

• 8+ years of experience in Cloud Engineering or DevOps roles.
• Bachelor's degree in Computer Science, Engineering, or equivalent experience.
• Proficiency with containerization (Docker, Kubernetes) and orchestration.
• Strong experience with declarative management tools like Terraform or Crossplane.
• Experience with major cloud platforms (AWS, Azure, or GCP).
• Scripting and programming proficiency in Go, Python, or Bash.

Nice to have

• Experience with monitoring tools like Prometheus, Grafana, or OpenTelemetry.
• Knowledge of cloud security best practices and compliance.
• Experience with agile development methodologies.

Culture & Benefits

• Commitment to a collaborative, "Customer First" culture.
• Flexible work arrangements within a distributed workforce model.
• Opportunity to work with cutting-edge AI-enabled tooling and processes.
• Focus on continuous innovation and professional growth.