DevOps Lead

About the Job

Join Impala AI, an innovative startup building a fully-managed LLM-inference platform, that enables data heavy enterprises to perform any AI task at any scale without limits.

We’re looking for a hands-on DevOps Lead to join our founding team. You’ll be the first DevOps hire, responsible for building our entire DevOps foundation - from CI/CD pipelines to large-scale distributed infrastructure. As the company scales, you’ll lead and grow a team of DevOps engineers to support our rapidly expanding AI platform.

This is a rare opportunity to own the full DevOps vision at a fast-growing AI infrastructure startup- architecting, automating, and scaling systems that power adaptive compute across multiple clouds and regions.

What You’ll Do

• Build and own the DevOps function end-to-end, from infrastructure automation to observability and deployment.
• Design, implement, and maintain scalable, secure, and resilient systems for managing large-scale ephemeral AI workloads.
• Architect and manage BYOC (Bring Your Own Cloud) deployment models across multiple cloud environments.
• Establish and manage CI/CD pipelines for rapid and reliable delivery across distributed services.
• Lead cloud cost optimization and performance tuning for GPU-intensive workloads.
• Collaborate with backend, research, and product teams to ensure seamless infrastructure integration.
• Define and implement best practices for security, compliance, and infrastructure reliability.
• Build, mentor, and lead a growing DevOps team as the organization scales.

What You’ll Bring

• 5+ years of DevOps or Cloud Infrastructure experience, including managing complex distributed systems.
• Proven experience designing and automating infrastructure using Terraform, Kubernetes, Helm, or similar tools.
• Strong programming/scripting experience in Python and Bash.
• Deep understanding of cloud environments (AWS, GCP, Azure) and multi-cloud architecture.
• Previous leadership or team management experience.
• Demonstrated ability to build systems from scratch and scale them to production-level reliability.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Excellent problem-solving, communication, and collaboration skills.
• A hands-on builder mindset , you’re comfortable being both strategic and deeply technical.

Bonus Points

• Experience managing GPU clusters, HPC, or large-scale AI training/inference workloads.
• Expertise in distributed compute orchestration and performance optimization.
• Familiarity with BYOC deployment models.