Applied AI Specialist-Cloud FullStack

Introduction

A career at IBM Consulting is built on enduring client partnerships and close collaboration across the globe. You’ll work with leading organizations across industries, supporting them in shaping their hybrid cloud and AI strategies. Backed by strategic partners, IBM technology, and Red Hat, you’ll gain the capabilities to drive meaningful transformation and strengthen client outcomes. At IBM Consulting, curiosity powers performance—you’ll be encouraged to challenge the status quo, pursue new perspectives, and develop inventive solutions that produce tangible results. Our growth and empathy-centered culture supports your long-term development while recognizing the value of your individual skills and experiences.

Your Role And Responsibilities

As an Applied AI Specialist: Cloud FullStack, you will design, build, and continuously enhance cloud-native and hybrid applications that convert client needs into scalable, secure, production-ready solutions. You will collaborate with digital workers and intelligent agents to deliver solutions, leverage an AI-First mindset, and follow established methodologies.

Your Primary Responsibilities Will Include

• Solution Design: Designing and building cloud-native and hybrid applications that satisfy client requirements while remaining scalable, secure, and production-ready.
• Application Development: Applying an AI-First mindset to automate scaffolding, dependency management, API definition, and validation, along with database design and validation.
• Pipeline Operation: Designing and operating CI/CD and GitOps pipelines using IaC and DevSecOps controls to support production readiness and improve cutover quality.
• Quality Engineering: Carrying out unit, module, and functional testing with testing agents and synthetic data to maintain quality and reliability.
• Incident Resolution: Using AI agents to examine logs and stack traces in order to triage and resolve incidents and defects across different stages.
  
  

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.