Applied AI Specialist-Cloud FullStack

Introduction A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences. Your Role And Responsibilities As an Applied AI Specialist: Cloud FullStack, you will design, build, and evolve cloud-native and hybrid applications that translate client requirements into scalable, secure, and production-ready solutions. This role involves collaborating with digital workers and intelligent agents to deliver solutions, applying an AI-First mindset and following established methodologies. Your Primary Responsibilities Will Include Solution Design: Designing and building cloud-native and hybrid applications that meet client requirements and are scalable, secure, and production-ready. Application Development: Applying an AI-First mindset to automate scaffolding, dependency management, API definition, and validation, as well as database design and validation. Pipeline Operation: Designing and operating CI/CD and GitOps pipelines with IaC and DevSecOps controls to ensure production readiness and cutover quality. Quality Engineering: Performing unit, module, and functional testing using testing agents and synthetic data to ensure quality and reliability. Incident Resolution: Analyzing logs and stack traces using AI agents to triage and resolve incidents and defects across different phases. Preferred Education Master's Degree Required Technical And Professional Expertise Cloud Application Development: Exposure to designing and building cloud-native and hybrid applications that meet client requirements and are scalable, secure, and production-ready. AI-First Mindset: Experience applying AI-First mindset to automate scaffolding, dependency management, API definition, and validation, as well as database design and validation. CI/CD Pipeline Operation: Exposure to designing and operating CI/CD and GitOps pipelines with IaC and DevSecOps controls to ensure production readiness and cutover quality. Quality Assurance: Experience performing unit, module, and functional testing using testing agents and synthetic data to ensure quality and reliability. Hyperscaler Platforms: Exposure to hyperscalers such as AWS, Azure, and Red Hat OpenShift, and deployment models to architect resilient and cost-optimized full-stack and integration patterns. Preferred Technical And Professional Experience Additional AI Tools: Exposure to other AI tools and technologies can be beneficial. Advanced Testing Methods: Familiarity with advanced testing methods and techniques is desirable. Emerging Technologies: Knowledge of emerging technologies and trends in cloud and AI can be advantageous.