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Role Description

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. This is a hands-on development role with technical leadership responsibilities and with company-wide impact.

• 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

Qualifications

• 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

Enhanced Qualifications (Nice to Have)

• 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

Salary Range

$180,000 to $210,000 base compensation depending on experience and stock options. Salary will be commensurate with an individual's skills, training, years of experience, and in line with internal compensation bands.

Location

This position can be performed remotely from anywhere in the United States.

Our Commitments

• Creating a diverse and inclusive workplace that is welcoming, supportive, affirming and respectful
• Empowering employees to solve problems and work together to make a difference
• Providing mentorship and growth opportunities as part of a collaborative team
• A flexible work environment with flexible paid time off
• Competitive compensation and benefits, including health, dental, vision, and employer-match 401k