Senior Azure AI Engineer

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Infosys

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Job Summary


Salary
₹60,469 - ₹101,719 / Monthly EST

Job Type
-

Seniority

Years of Experience
Information not provided

Tech Stacks
Azure CI

Job Description

Azure Machine Learning, Azure Cognitive Services, Azure OpenAI Service, Prompt Engineering, MLOps

  • 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.

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