Senior Site Reliability Engineer

We are looking for a dynamic Senior Site Reliability Engineer (SRE) to join our team. The Site Reliability Engineer (SRE) will manage, monitor, and optimize clusters on Kubernetes. Together, we’re accelerating our clients’ digital transformation through the building and deployment of data-driven, scalable AI solutions. The ideal candidate will have a deep understanding of Kubernetes, Cloud Infrastructure, and Infrastructure as Code (IaC) practices. You will be responsible for ensuring the reliability and scalability of our clients’ Kubernetes clusters and Cloud Infrastructure. The person in this role will work onsite at Peterson Space Force Base.

Responsibilities

The responsibilities include, but are not limited to:

• Monitor and Manage Kubernetes Clusters: Ensure the stability, health, and scalability of Kubernetes Clusters, deploying applications and services on Kubernetes
• Kubernetes Management: Deploy, monitor, and scale applications on Kubernetes clusters. Maintain Helm charts, manage services, and ensure resource allocation for optimal cluster performance
• Containerization & Deployment: Design and maintain Docker-based microservices architecture, ensuring consistent and reproducible deployments across staging, QA, and production environments
• Cloud Infrastructure Management: Work with leading Cloud Platforms (AWS, Azure and/or Google Cloud Platform) to set up, configure, and manage infrastructure resources using Infrastructure as Code (Terraform, CloudFormation, etc.)
• Monitoring & Incident Response: Set up monitoring solutions, define alerts, and manage the incident response process for any issues related to Jenkins or Kubernetes clusters
• Automate Infrastructure Processes: Build automation tools for scaling, monitoring, and maintaining infrastructure using modern tools like Terraform, Ansible, Linux, or equivalent
• Collaborate Across Teams: Work closely with development, services, and operations teams to ensure a seamless integration between application development, deployment, and infrastructure
• Security & Compliance: Ensure all systems follow best practices in terms of security and compliance with relevant regulations. This includes role-based access, encryption, and automated vulnerability scanning

Requirements

• Active TOP SECRET clearance or higher is required
• Bachelor’s degree (or equivalent) in computer science or related discipline
• A minimum of five (5) years of experience working with on-premise and off-premise cloud environments
• Experience with AWS and/or Azure
• Hands-on experience with a range of open-source technologies, such as Linux, Docker, Kubernetes, K8s, Terraform, Helm, PostgreSQL, or similar technologies
• Ability to program (structured and OOP) using one OR more high-level languages, such as Python, Java, C/C++, Ruby, and JavaScript
• Experience with distributed storage technologies such as NFS, HDFS, Ceph, and Amazon S3, as well as dynamic resource management frameworks (Apache Mesos, Kubernetes, Yarn)
• Proactive approach to identifying problems, performance bottlenecks, and areas for improvement
• Ability to lead and work independently in an Agile/Scrum environment
• Real passion for developing team-oriented solutions to complex engineering problems
• Ability to thrive in an autonomous, empowering and exciting environment
• Great verbal and written communication skills to collaborate multi-functionally and improve scalability
• The ability to work on multiple concurrent projects is essential. Strong self-motivation and the ability to work with minimal supervision
• Must be a team-oriented individual, energetic, result & delivery oriented, with a keen interest in quality and the ability to meet deadlines
• Must have demonstrated experience serving in, or supporting, a federal agency that requires a Top Secret clearance.

Desired Skills

• Hands-on experience deploying and operating applications using IaaS and PaaS on major cloud providers, such as Amazon AWS, Microsoft Azure, or Google Cloud Services
• Experience with deep learning, natural language processing, computer vision, or reinforcement learning
• Convey highly technical concepts and information in written form to technical and non-technical audiences