Principal Data Infrastructure Engineer (AI)

TL;DR

Principal Data Infrastructure Engineer (AI/Big Data): Architecting and maintaining scalable big data infrastructure for mission-critical AI applications with an accent on platform engineering and SRE practices. Focus on building self-service big data platforms, optimizing data pipelines, and integrating LLMs into DevOps workflows.

Location: Mountain View, United States. Expected to work from the office at least four days per week.

Salary: $188,000 – $304,200 per year

Company

hirify.global is building intelligent systems across agents, applications, and infrastructure to make artificial intelligence accessible to all.

What you will do

• Architect and maintain scalable, reliable, and observable Big Data Infrastructure for AI applications.
• Implement DevOps and SRE best practices, including automated deployments, service monitoring, and incident response.
• Build a self-service big data platform to empower data engineers, platform engineers, and researchers.
• Develop robust CI/CD pipelines and automate infrastructure provisioning using Bicep, Terraform, or ARM.
• Optimize system performance across storage, compute, and analytics layers.
• Collaborate with Data Scientists and AI Researchers to deliver secure and seamless big data workflows.

Requirements

• Master’s Degree + 4 years or Bachelor’s Degree + 6 years of experience in data engineering, software development, or data modeling.
• Must be based in or within commuting distance of Mountain View, US.
• Hands-on experience managing and scaling distributed systems and deploying containerized applications using Kubernetes and Helm/Kustomize.
• Proficiency in scripting and automation using Python, Bash, or PowerShell.
• Experience with cloud-native infrastructure (Azure, AWS, or GCP) and modern data platforms like Databricks.
• Deep understanding of Spark compute engines, distributed file systems, and messaging systems (Kafka, Event Hub).

Nice to have

• Experience integrating LLMs into DevOps workflows for incident response and operational intelligence.
• Proficiency in prompt engineering techniques to optimize LLM interactions.
• Familiarity with modern web stacks including TypeScript, Node.js, and React.
• Exposure to agentic workflows and deep learning frameworks.

Culture & Benefits

• Culture of inclusion built on respect, integrity, and accountability.
• Focus on a growth mindset and continuous learning.
• Opportunity to work on the most challenging AI infrastructure questions of our time.
• Comprehensive corporate benefits package.