- Build and deploy intelligent solutions on Microsoft Azure that turn data into real world impact
- In this role you ll collaborate closely with product engineering and business teams to design prototype and deliver AI capabilities using Azure s AI services and Azure AI Studio
- You ll help shape end to end AI workflows from experimentation to production while keeping reliability scalability and responsible AI practices in focus
- If you enjoy solving meaningful problems iterating quickly with stakeholders and translating ideas into working AI features this is a great opportunity to grow your cloud AI expertise in a supportive collaborative environment
- Design develop and integrate AI solutions using Azure AI services aligned to business requirements
- Build and iterate AI prototypes and workflows using Azure AI Studio improving solution quality through experimentation and evaluation
- Implement end to end AI pipelines including data preparation model service selection prompt workflow design where applicable and deployment to Azure environments
- Collaborate with cross functional teams to define use cases success metrics and acceptance criteria for AI features
- Ensure solutions meet performance scalability security and compliance expectations in cloud deployments
- Monitor and troubleshoot AI solutions in production driving continuous improvement through feedback loops and iterative releases
- Document architectures workflows and operational runbooks to support maintainability and knowledge sharing
- Minimum Qualifications
- Bachelor s degree in B
- Tech or equivalent in Computer Science IT Engineering or a related field
- 2 5 years of experience delivering software or cloud solutions with hands on exposure to Azure AI services
- Working experience with Azure AI Studio for building testing and refining AI solutions workflows
- Strong understanding of cloud fundamentals APIs integration patterns and production grade engineering practices
- Ability to communicate clearly with technical and non technical stakeholders and work effectively in a team setting
- Preferred Qualifications
- Experience designing solution architectures for AI workloads on Azure including environment setup deployment patterns and operational considerations
- Familiarity with responsible AI practices such as safety privacy bias considerations and governance controls in enterprise settings
- Experience with evaluation approaches for AI solutions quality latency cost and iterative optimization based on measurable outcomes
- Exposure to CI CD and automation for deploying and maintaining AI solutions in Azure
- Proven ability to translate ambiguous problem statements into implementable AI workflows and deliver incrementally with stakeholders
- Azure Machine Learning Azure Cognitive Services Azure OpenAI Service Prompt Engineering MLOps
Technology->AI Hyperscalers->Azure Agentic AI Services->Azure AI
