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Consultant - Full Stack AI Application Developer

https://www.microsoft.com/ Logo

Microsoft Corporation

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Location:
India , Hyderabad

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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Job Description:

Microsoft Industry Solutions – Global Center for Innovation and Delivery (GCID) delivers end‑to‑end, industry‑aligned solutions by accelerating customer adoption of Microsoft technologies. With a global team of 1,000+ professionals, GCID offers early‑career engineers a collaborative environment to work on real‑world customer challenges and build consulting, cloud, and application development skills. As a Consultant – Full Stack AI Application Developer (Azure), you will contribute to the design, development, and deployment of modern cloud‑based applications, partnering with senior engineers and architects. This role is ideal for developers eager to strengthen full‑stack skills, deepen Azure expertise, and gain exposure to AI‑enabled application patterns in enterprise delivery.

Job Responsibility:

  • Design and build cloud-native, full-stack applications on Microsoft Azure, contributing across UI, API, services, and data layers with high-quality, secure, and scalable code
  • Collaborate with architects and senior consultants to translate business requirements into technical designs and implementation plans
  • participate in design reviews and solution walkthroughs
  • Own feature delivery end-to-end: estimate effort, implement features, write unit/integration tests, perform code reviews, and support deployment through CI/CD pipelines
  • Integrate backend services and data platforms, implement RESTful APIs, and ensure performance, reliability, and observability (logging, metrics, traces) for production readiness
  • Apply security, compliance, and Responsible AI principles across application development and operations, following Microsoft and customer governance standards
  • Identify technical risks and dependencies early
  • raise and help mitigate issues, support technical escalations, and contribute to contingency plans for smooth delivery
  • Reuse and contribute to shared frameworks and IP, leveraging best practices, accelerators, and patterns to improve delivery speed and predictability
  • Collaborate cross-functionally (e.g., project leads, delivery managers, account teams) to articulate technical value, support adoption, and ensure customer outcomes
  • Continuously learn and improve, adopt modern engineering practices (DevSecOps, automation, testing, cloud monitoring) and sharing learnings with the team

Requirements:

  • 4-10 years of professional software development experience
  • Bachelor's degree in computer science, Engineering, or a related discipline, or equivalent practical experience
  • Microsoft or cloud certifications are preferred, including but not limited to: MCSD/MCAD/MCSE, AZ-204, AI-900, AI-102, or equivalent entry- to mid-level cloud and AI certifications
  • Hands-on experience designing and building applications using .NET (C#), .NET Web APIs, Node.js with modern front-end technologies such as JavaScript or TypeScript, and frameworks like Angular or React
  • Strong understanding of application development across UI, API, service, integration, and data layers
  • Experience building and consuming RESTful services and integrating backend systems
  • Working knowledge of relational databases such as Azure SQL, Azure Cosmos DB, PostgreSQL, Azure SQL managed Instance or Azure Database for MySQL, including data access and performance considerations
  • Solid foundation in software engineering principles, including clean code, debugging, testing, and problem-solving
  • Hands-on experience integrating AI capabilities into applications, such as search, chat, recommendations, or content generation using AI services or APIs
  • Practical knowledge of Azure AI services, including Azure AI Foundry and Azure AI Search, and understanding of RAG (Retrieval-Augmented Generation) patterns
  • Experience with RAG pipelines, vector search workflows, or agent-based patterns using tools such as Semantic Kernel, LangChain, or similar frameworks
  • Experience with prompt engineering and optimization to build reliable, high-quality AI-driven application workflows
  • Working knowledge of Python for implementing AI workflows, automation, or AI-assisted application components
  • Understanding and application of Responsible AI principles in designing and delivering AI-enabled solutions
  • Experience working with Microsoft Azure for application hosting, configuration, and deployment
  • Familiarity with CI/CD pipelines, source control (Git), and automated build and release processes
  • Basic experience with application monitoring, logging, and troubleshooting in cloud environments
  • Understanding secure application development practices, including authentication and authorization
  • Exposure to evaluation and tuning techniques for improving AI response quality and reliability
  • Familiarity with microservices and serverless architectures, including Azure Functions, containers, or Kubernetes
  • Awareness of deployment strategies such as blue/green or canary releases
  • Exposure to end-to-end observability concepts (metrics, traces)
  • Experience with open-source technologies or familiarity with platforms beyond Azure (e.g., Java, AWS, or Google Cloud Platform)
  • Domain exposure to industries such as financial services, healthcare, manufacturing, or retail
  • Ability to work closely with senior consultants, architects, and customers to co-create innovative solutions with customers to help solve their business challenges
  • Strong communication skills to explain technical concepts to business stakeholders
  • Comfortable working in ambiguous environments, learning quickly, and adapting to change
  • Eagerness to build engineering excellence, reusable components, and best practices
  • Strong interest in continuous learning and technical certifications
  • Curiosity to explore emerging data and AI technologies
  • Willingness to receive feedback, grow technical depth, and expand ownership over time

Nice to have:

  • Exposure to evaluation and tuning techniques for improving AI response quality and reliability
  • Familiarity with microservices and serverless architectures, including Azure Functions, containers, or Kubernetes
  • Awareness of deployment strategies such as blue/green or canary releases
  • Exposure to end-to-end observability concepts (metrics, traces)
  • Experience with open-source technologies or familiarity with platforms beyond Azure (e.g., Java, AWS, or Google Cloud Platform)
  • Domain exposure to industries such as financial services, healthcare, manufacturing, or retail

Additional Information:

Job Posted:
May 16, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
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