Senior Software Engineer, DevOps
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 Senior Software Engineer, DevOps 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 deep technical ownership and cross-team visibility. This engineer will build and maintain the systems that keep our platform running, help shape infrastructure and deployment best practices, and support less experienced 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.
Requirements
- 8+ years of development experience including experience in platform engineering, SRE, or distributed systems, with demonstrated senior-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
- Strong problem-solving skills and attention to detail
- Strong communication and collaboration skills, with experience contributing to 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
- Support the deployment and management of containerized applications using Kubernetes, ensuring optimal performance and availability
- Contribute to strategic planning on how infrastructure solutions evolve to match Data Center partner requirements
- Design, implement, and maintain 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
- 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
Benefits
- health, dental, vision, and employer-match 401k
- flexible paid time off
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What This Job Offers
Job Type
Full-time
Career Level
Senior
