Applied AI Specialist-Cloud FullStack

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.

Required Education:

Bachelor's Degree

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.

****Years of Experience:****5 - 10