Site Reliability Engineer at Radiant Systems Solutions, Inc — NeverHard

Duration: 12+ months (Total Hours: 8,992.00) Description As a Developer focused on Platform Engineering and AI/ML, you will design, implement, and operate the cloud‑native infrastructure that powers next‑generation Business Data Cloud solutions. You Will Collaborate with engineering and operations to design, and maintain build systems, CI/CD pipelines, and deployment tooling Develop high‑quality, secure backend services and automation tools supporting end‑to‑end lifecycle of AI/ML features Provide infrastructure expertise, best practices for cloud integration, CI/CD automation, and modern service architecture. Translate complex requirements from cross‑functional stakeholders into technical designs and executable implementation plans. Lead design reviews, produce clear technical documentation, provide peer feedback, and represent your work through demos, presentations, and retrospectives. Contribute to intelligent technology portfolio by enabling reliable, data‑driven decision making at scale. What You Bring 1-2 years of hands‑on experience in SRE/DevOps, systems engineering, cloud operations, or automation in enterprise environments. Proficiency in cloud platforms (SAP BTP, AWS, GCP, Azure) and container technologies (Kubernetes, Cloud Foundry, Docker, cloud databases, and data/event pipelines). Experience building and operating complex CI/CD pipelines (e.g., Jenkins, Argo CD, Flux CD, GitHub Actions) and automated delivery processes Strong understanding of networking fundamentals and experience with modern load balancers (e.g., HAProxy, NGINX). Ability to write maintainable, production‑grade code in languages such as Python, Java, or similar. Excellent communication skills with the ability to articulate technical concepts to both technical and non‑technical audiences. Preferred Qualifications Designing highly available, horizontally scalable distributed systems; traffic management, autoscaling, and progressive delivery patterns. Ability to architect modular, reusable distributed systems. Experience implementing Generative AI services, ML Ops tooling, or AI‑driven enterprise applications. Master’s degree or equivalent experience. #J-18808-Ljbffr