Principal Data Infrastructure Engineer (AI)

TL;DR

Principal Data Infrastructure Engineer (AI): Building and optimizing scalable, reliable, and observable Big Data Infrastructure for mission-critical AI applications and ML pipelines with an accent on DevOps/SRE best practices, automation, and distributed systems. Focus on architecting a self-service big data platform, proactively identifying and resolving bottlenecks, and optimizing system performance across all layers.

Location: Redmond, United States. Must be able to commute to a designated Microsoft office in the U.S. at least four days per week.

Salary: USD $139,900 – $274,800 per year

Company

hirify.global is dedicated to building systems with true artificial intelligence across agents, applications, services, and infrastructure, aiming to make AI accessible to all consumers, businesses, and developers.

What you will do

• Architect and maintain scalable, reliable, and observable Big Data Infrastructure for mission-critical AI applications.
• Champion DevOps and SRE best practices, including automated deployments, service monitoring, and incident response.
• Build a self-service big data platform empowering data and platform engineers and researchers.
• Develop robust CI/CD pipelines and automate infrastructure provisioning using Infrastructure as Code tools.
• Collaborate with Data Engineers, Data Scientists, AI Researchers, and Developers to deliver secure, seamless big data workflows.
• Proactively identify and resolve bottlenecks in data pipelines and optimize system performance across storage, compute, and analytics layers.

Requirements

• Master’s Degree in Computer Science or related field with 4+ years, OR Bachelor’s Degree with 6+ years experience in business analytics, data science, software development, data modeling, or data engineering.
• 4+ years in Big Data Infrastructure, DevOps, SRE, or Platform Engineering.
• 3+ years of hands-on experience managing and scaling distributed systems, from bare-metal to cloud-native environments.
• 2+ years deploying containerized applications using Kubernetes and Helm/Kustomize.
• Solid scripting and automation skills using Python, Bash, or PowerShell.
• Proven success in CI/CD pipeline management, release automation, and production troubleshooting.
• English: B2 proficiency required.

Nice to have

• Experience working with Databricks for scalable data processing and analytics.
• Familiarity with security practices including IAM, OAuth, and Kerberos administration.
• Proven experience with cloud-native infrastructure across Azure, AWS, or GCP.
• Deep understanding of data storage and processing technologies (Relational & NoSQL databases, Key-value stores, Spark compute engines, Distributed file systems, Messaging systems).
• Practical experience integrating LLMs (e.g., GPT-based models) into daily workflows and solid grasp of prompt engineering techniques.

Culture & Benefits

• Foster a growth mindset, innovate to empower others, and collaborate to achieve shared goals.
• Uphold values of respect, integrity, and accountability to create a culture of inclusion.