Senior Azure AI Engineer

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

Education: Bachelor of Engineering,Bachelor Of Technology

Preferred skills: Technology->AI Hyperscalers->Azure Agentic AI Services->Azure AI