Applied AI Specialist-Cloud FullStack
Hakkōda, an IBM Company
This job at a glance
- Who can apply
- Freshers
- Must know
- REST APIsCI/CDAWSAzureGitOperations
- Work
- On-site in Bengaluru
- Pay
- Not stated by the employer.
- Listed
- 7 Nov 2026 · still open
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About the Role
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.
Key Responsibilities
- 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.
Requirements & Tech Stack
- 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.
- 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.
Technologies Mentioned:
Amazon Web Services, Artificial Intelligence, Database Design, Functional Testing, Integration, Delivery Pipelines, Quality Assurance, Reliability Testing, Validation, Azure, DevSecOps, Continuous Integration/Continuous Delivery, Red Hat OpenShift, Application Programming Interface, Dependency Management, Emergent Technologies, Git Operations, Synthetic Data, Production Readiness, Cloud Development.