Applied Ai Specialist-Cloud Fullstack
IBM · Pune · onsite · Posted 58d ago
Undisclosed10–19 yrsfulltimeSourced from
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About this role
Your Role and Responsibilities:
Your primary responsibilities will include:
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:
10 - 19
10 - 19
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Skills
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