Principal Software Engineer, DevOps

Utilidata•Ann Arbor, MI

2d•$180,000 - $210,000•Remote

About The Position

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically orchestrate power and unlock more compute capacity from existing energy infrastructure. For over a decade, we have applied AI to the electric grid — bringing real-time visibility and power-flow control to complex energy infrastructure. Our Karman platform, built on a custom NVIDIA module, brings that same capability to AI data centers, giving operators a way to better use the power already available to them. We are seeking a DevOps Engineer to help design, build, and operate Utilidata’s off-device platform that ingests, processes, and serves data flowing from edge AI devices. The role will build and maintain infrastructure across on-premises and cloud environments - bridging edge deployments with cloud-based data processing to support analytics, operations, and ML workloads at scale. This is a hands-on development role with technical leadership responsibilities and with company wide impact. This engineer will architect and maintain the systems that keep our platform running, set technical direction for infrastructure and deployment practices, and mentor engineers. This engineer will partner closely with on device, and ML teams to ensure our off-device platform is resilient, well-instrumented, and ready to scale. This is a remote position based in the United States, working with distributed teams across the country.

Requirements

8+ years of development experience including extensive experience in platform engineering, SRE, or distributed systems, with clear senior or principal-level impact
Experience designing and operating infrastructure across on-premises and cloud environments
Strong proficiency in container orchestration, particularly Kubernetes
Strong proficiency with AWS services and architecture
Hands-on experience with Terraform for infrastructure automation
Familiarity with monitoring tools (Prometheus, Grafana, or similar) and observability best practices
Excellent problem-solving skills, leadership abilities, and attention to detail
Strong communication and collaboration skills, with experience in driving technical outcomes
Willingness to travel up to 20% of time

Nice To Haves

Bachelor's degree in Computer Science, Engineering, or a related field
Experience supporting or enabling MLOps platforms, model deployment pipelines, or ML-adjacent infrastructure
AI Workload scheduling using Kubernetes
Knowledge of Apache Spark for large-scale data processing
Knowledge of database technologies (SQL, NoSQL)
Understanding of networking concepts and security best practices

Responsibilities

Oversee the deployment and management of containerized applications using Kubernetes, ensuring optimal performance and availability
Contribute to strategic planning regarding how the infrastructure solutions evolve to match the requirements of Data Center partners
Lead the design, implementation, and maintenance of scalable and reliable systems on AWS and/or on-premise
Utilize Terraform for infrastructure as code to automate the provisioning and management of cloud resources
Monitor system performance and uptime, ensuring systems meet established service level objectives (SLOs)
Support SOC2 security compliance requirements for data handling
Mentor and guide team members in DevOps practices, promoting a culture of reliability and excellence
Advocate for automation of operational tasks to enhance efficiency and reduce manual intervention
Collaborate with cross-functional teams to build and maintain CI/CD pipelines
Troubleshoot and resolve complex production issues, conducting root cause analysis and implementing corrective actions
Participate in on-call rotations and incident response teams
Assist in capacity planning, performance tuning, and technical decision-making
Drive continuous improvement initiatives for processes and infrastructure