CloudOps Lead Engineer

Position Information Type: Contract Position: CloudOps Lead Engineer Location: Plano, TX (Onsite) Job Description: 12+ Years of Experience Required We are looking for a motivated and hands-on Cloud Ops Engineer to join our team and play a critical role in deploying, operating, and maintaining our cloud-based products. This role is essential to ensuring smooth deployments, high system reliability, and strong operational performance across our environments. The ideal candidate has a strong “want-to-learn” mindset, is eager to deeply understand our ecosystem and architecture, and demonstrates ownership, leadership, and the ability to drive initiatives independently. Required Skills & Qualifications Technical Skills • Hands-on experience with cloud platforms (Azure. • Strong scripting skills (e.g., Python, Bash, PowerShell, or similar). • Experience with deployment pipelines, automation, and monitoring tools. • Solid understanding of cloud infrastructure, networking, and application operations. LLM & AI Experience • Practical experience working with Large Language Models (LLMs). • Familiarity with applying LLMs to engineering or operational workflows is required. Professional Attributes • Strong desire to learn and deeply understand complex systems. • Self-starter with the ability to take ownership and drive initiatives independently. • Demonstrates leadership, accountability, and problem-solving mindset. • Strong collaboration and communication skills Key Responsibilities • Cloud Operations & Deployments • Support and manage cloud deployments to ensure reliable, repeatable, and high-quality releases. • Own day-to-day cloud operational health, including uptime, performance, and stability. • Work closely with engineering teams to support product deployments and operational readiness. • Automation & Scripting • Design, develop, and maintain automation scripts to improve deployment quality, efficiency, and consistency. • Continuously enhance CI/CD and operational workflows through scripting and tooling. • Reduce manual effort and operational risk through automation-first approaches. • Monitoring & System Health • Implement and maintain monitoring, alerting, and logging to ensure system health and performance. • Proactively identify issues, perform root cause analysis, and drive permanent fixes. • Ensure systems are scalable, resilient, and performant. • Architecture & Ecosystem Understanding • Develop a deep understanding of the platform architecture, cloud ecosystem, and dependencies. • Contribute to operational best practices, standards, and continuous improvement initiatives. • Act as a self-starter who can independently identify gaps and propose solutions. • LLM & AI Enablement • Apply Large Language Models (LLMs) in cloud operations use cases such as automation, observability, diagnostics, or operational intelligence. • Stay current with advancements in LLMs and AI-driven tooling and apply them pragmatically within the Cloud Ops domain. • Collaborate with engineering teams to integrate LLM-based capabilities into operational workflows.