Principal Data Infrastructure Engineer (AI)

TL;DR

Principal Data Infrastructure Engineer (AI): Architecting and maintaining scalable, reliable, and observable Big Data Infrastructure for mission-critical AI applications with an accent on DevOps/SRE best practices and self-service platform enablement. Focus on developing robust CI/CD pipelines, automating infrastructure provisioning, and optimizing system performance across storage, compute, and analytics layers.

Location: Redmond, United States (Hybrid - expect to work from office at least four days per week if within 50-mile commute of a designated Microsoft office in the U.S.)

Salary: USD $139,900 – $274,800 per year (up to $304,200 for specific high-cost locations in the U.S.)

Company

hirify.global is pushing the boundaries of AI, building systems with true artificial intelligence across agents, applications, services, and infrastructure, aiming to make AI accessible to all.

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 to empower data and platform engineers and researchers.
• Develop robust CI/CD pipelines and automate infrastructure provisioning using Infrastructure as Code tools (Bicep, Terraform, ARM).
• Collaborate with Data Engineers, Data Scientists, AI Researchers, and Developers to deliver secure, seamless big data workflows.
• Proactively identify and resolve bottlenecks and optimize system performance across storage, compute, and analytics layers.

Requirements

• Master’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years experience, OR Bachelor’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 6+ years experience in business analytics, data science, software development, data modeling, or data engineering
• 4+ years experience 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.

Nice to have

• Experience working with Databricks for scalable data processing and analytics.
• Familiarity with security practices in infrastructure environments, 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 including Relational & NoSQL databases, Spark compute engines, Distributed file systems (e.g., HDFS, ADLS Gen2), and Messaging systems (e.g., Event Hub, Kafka, RabbitMQ).
• Practical experience integrating LLMs (e.g., GPT-based models) into daily workflows and solid grasp of prompt engineering techniques.

Culture & Benefits

• Opportunity to work with passionate individuals on challenging AI questions of our time.
• Work in a culture of inclusion where everyone can thrive, built on values of respect, integrity, and accountability.
• Innovate to empower others and collaborate to realize shared goals.
• Access to additional benefits and pay information.