Senior Software Engineer, DevOps
- 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
- 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
- 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
Utilidata values the diversity of our team. We provide equal employment opportunities without regard to race, color, religion, creed, sex, gender, sexual orientation, gender identity or expression, national origin, age, physical disability, mental disability, medical condition, pregnancy or childbirth, sexual orientation, genetics, genetic information, marital status, or status as a covered veteran or any other basis protected by applicable federal, state and local laws. We are committed to:
- 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
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