2 months ago
Mumbai, IndiaSenior
Responsibilities
- Engage customer IT and business leaders to understand application, data, and AI priorities and design secure, scalable solutions.
- Lead architecture design, proof-of-concept, minimum viable product, and technical delivery engagements across Azure AI, App Services, GitHub, and data platforms.
- Own end-to-end technical delivery results and collaborate on customer success and consumption plans.
- Drive adoption, next-best actions, and incremental pipeline aligned with enterprise support priorities.
- Create reusable intellectual property and contribute to centralized IP development.
- Provide delivery oversight and escalation support for AI and application innovation engagements.
- Lead the health, resiliency, security, optimization, and production readiness of mission-critical workloads.
- Share customer feedback with engineering teams to influence product improvements and remove adoption blockers.
- Deliver technical workshops, readiness activities, skilling, and recommendations for solution performance, maintainability, and reliability.
- Maintain expertise in Azure, AI, GitHub, and cloud-native development; contribute to technical communities and mentor others.
- Build enterprise generative AI solutions using open-source LLMs, RAG architectures, vector databases, AI agents, and agentic workflows.
Requirements
- Bachelor's degree in Computer Science, Information Technology, Engineering, Business, or a related field and 8+ years of relevant experience; or a master's degree in those fields and 8+ years of relevant experience; or equivalent experience.
- 8+ years of experience in a customer-facing role.
- 8+ years of experience working on technical projects.
- Technical cloud certification, such as Azure, Amazon Web Services, Google, or security certification.
- Hands-on experience with open-source LLMs including Llama, Mistral, DeepSeek, Qwen, and Gemma.
- Experience designing and implementing RAG architectures with LangChain, LlamaIndex, vector databases, and enterprise knowledge sources.
- Experience building AI agents and agentic workflows with LangGraph, CrewAI, AutoGen, and MCP and integrating them into enterprise applications and business processes.
- Ability to work with Azure AI Foundry, AKS, App Service, Cosmos DB, Azure SQL, PostgreSQL, APIM, and GitHub.
Tech Stack
Categories
Solutions Engineering
About Microsoft
Microsoft develops operating systems, productivity software, cloud services, developer tools, and consumer devices for individuals, enterprises, and governments. Its main products include Windows, Microsoft 365, Azure, Visual Studio/GitHub, Xbox, and LinkedIn; revenue comes from software subscriptions and licenses, cloud consumption, hardware sales, and advertising. Founded in 1975 and headquartered in Redmond, Washington, Microsoft is a public company traded on Nasdaq.