Applied AI Specialist-Cloud FullStack

Introduction

A career with IBM Consulting is grounded in enduring client relationships and global teamwork. You will collaborate with leading organizations across industries to shape their hybrid cloud and AI initiatives. Backed by strategic partners, IBM technology, and Red Hat, you will have the capabilities to drive meaningful change and improve client outcomes faster. At IBM Consulting, curiosity drives performance—you’ll be encouraged to question the status quo, explore new perspectives, and develop solutions that deliver measurable results. Our growth and empathy culture supports your long-term career development, while recognizing and valuing your individual skills and experiences.

Your Role And Responsibilities

As an Applied AI Specialist: Cloud FullStack, you will design, build, and continuously improve cloud-native and hybrid applications that convert client needs into scalable, secure, production-ready solutions. The role includes working with digital workers and intelligent agents, using an AI-First mindset, and applying established methodologies to deliver outcomes.

Your Primary Responsibilities Will Include

• Solution Design: Designing and building cloud-native and hybrid applications aligned to client requirements, with scalability, security, and production readiness.
• Application Development: Using an AI-First mindset to automate scaffolding, dependency management, API definition, and validation, along with database design and validation.
• Pipeline Operation: Creating and managing CI/CD and GitOps pipelines with IaC and DevSecOps controls to support production readiness and enhance cutover quality.
• Quality Engineering: Conducting unit, module, and functional testing with testing agents and synthetic data to maintain quality and reliability.
• Incident Resolution: Using AI agents to analyze logs and stack traces, triage, and resolve incidents and defects across multiple stages.
  
  

Preferred Education

Master's Degree

Required Technical And Professional Expertise

• Cloud Application Development: Experience with designing and building cloud-native and hybrid applications that address client requirements and deliver scalability, security, and production readiness.
• AI-First Mindset: Hands-on experience applying an AI-First mindset to automate scaffolding, dependency management, API definition, and validation, as well as database design and validation.
• CI/CD Pipeline Operation: Experience with designing and operating CI/CD and GitOps pipelines using 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: Experience with hyperscalers such as AWS, Azure, and Red Hat OpenShift, and deployment models to design 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.