Experience
1 - 5 yrs
Salary (CTC)
₹15.4L - ₹22.1L
Job Location
Bengaluru, India
Vacancy
1
Designation
AI Engineer
Job Type
Not specified
Job Description
We are seeking a dynamic and technically strong AI Lead with 68 years of industry experience, including a minimum of 5 years in AI/ML and Conversational AI technologies, with a specific focus on Microsofts AI ecosystem
The ideal candidate will lead the design, development, and delivery of intelligent solutions using Azure OpenAI, Copilot Studio, Microsoft Bot Framework, and AI Foundry
Key Responsibilities: Lead end-to-end technical implementation of AI-driven projects using Microsoft AI tools: Azure OpenAI, Copilot Studio, and Bot Framework
Design and develop intelligent copilots, multi-turn chatbots, and custom GPT solutions integrated within enterprise tools such as Microsoft Teams, SharePoint, and Dynamics 365
Translate business requirements into technical architecture and AI flows using OpenAI APIs, prompt engineering, and integration with enterprise systems
Leverage AI Foundry to manage the AI lifecycle including model selection, deployment, monitoring, and optimization
Architect AI/ML solutions that use Retrieval-Augmented Generation (RAG), semantic search, and contextual memory frameworks (LangChain, Semantic Kernel, etc)
Collaborate with product owners and business analysts to identify high-value use cases and define solution roadmaps
Develop and execute POCs and MVPs with hands-on coding, configuration, and orchestration of LLMs and chatbot pipelines
Integrate with enterprise data sources via APIs, GraphQL, and Microsoft Graph to create holistic user experiences
Mentor junior developers and work with DevOps teams to ensure stable deployment, CI/CD, and performance monitoring
Create documentation and reusable components/templates for repeated use across the organization
Stay current on Microsofts AI advancements and recommend tools, features, or practices that improve time-to-value and performance
Must-Have Skills: 68 years of overall experience, including 5+ years in AI/ML or Conversational AI Deep hands-on knowledge of: Azure OpenAI services and APIs Copilot Studio for building Microsoft 365-integrated assistants Microsoft Bot Framework SDK/Composer for chatbot development Prompt engineering for LLM optimization Strong Python or Nodedot js development skills (for AI orchestration and integration) Experience with enterprise system integration using APIs (Microsoft Graph, REST, JSON, OAuth) Familiarity with Azure ML, Azure Cognitive Services, and Azure DevOps Ability to design RAG-based architectures, manage embeddings, and leverage vector databases (e-g
, Azure AI Search) Strong understanding of natural language processing (NLP) and foundational models (GPT, BERT) Excellent communication, leadership, and stakeholder engagement capabilities Good-to-Have Skills: Experience with Semantic Kernel or LangChain Working knowledge of AI Foundry for orchestrating AI pipelines Familiarity with Copilot extensibility and Teams App Studio Exposure to M365 Copilot APIs and custom plugin creation Knowledge of Responsible AI, data security, and compliance principles Familiarity with containerized deployment (Docker, Kubernetes) Experience in building dashboards and analytics (Kibana, Grafana) to visualize bot usage and performance Basic understanding of Power Platform (Power Automate, Power Apps) and its integration with AI
The ideal candidate will lead the design, development, and delivery of intelligent solutions using Azure OpenAI, Copilot Studio, Microsoft Bot Framework, and AI Foundry
Key Responsibilities: Lead end-to-end technical implementation of AI-driven projects using Microsoft AI tools: Azure OpenAI, Copilot Studio, and Bot Framework
Design and develop intelligent copilots, multi-turn chatbots, and custom GPT solutions integrated within enterprise tools such as Microsoft Teams, SharePoint, and Dynamics 365
Translate business requirements into technical architecture and AI flows using OpenAI APIs, prompt engineering, and integration with enterprise systems
Leverage AI Foundry to manage the AI lifecycle including model selection, deployment, monitoring, and optimization
Architect AI/ML solutions that use Retrieval-Augmented Generation (RAG), semantic search, and contextual memory frameworks (LangChain, Semantic Kernel, etc)
Collaborate with product owners and business analysts to identify high-value use cases and define solution roadmaps
Develop and execute POCs and MVPs with hands-on coding, configuration, and orchestration of LLMs and chatbot pipelines
Integrate with enterprise data sources via APIs, GraphQL, and Microsoft Graph to create holistic user experiences
Mentor junior developers and work with DevOps teams to ensure stable deployment, CI/CD, and performance monitoring
Create documentation and reusable components/templates for repeated use across the organization
Stay current on Microsofts AI advancements and recommend tools, features, or practices that improve time-to-value and performance
Must-Have Skills: 68 years of overall experience, including 5+ years in AI/ML or Conversational AI Deep hands-on knowledge of: Azure OpenAI services and APIs Copilot Studio for building Microsoft 365-integrated assistants Microsoft Bot Framework SDK/Composer for chatbot development Prompt engineering for LLM optimization Strong Python or Nodedot js development skills (for AI orchestration and integration) Experience with enterprise system integration using APIs (Microsoft Graph, REST, JSON, OAuth) Familiarity with Azure ML, Azure Cognitive Services, and Azure DevOps Ability to design RAG-based architectures, manage embeddings, and leverage vector databases (e-g
, Azure AI Search) Strong understanding of natural language processing (NLP) and foundational models (GPT, BERT) Excellent communication, leadership, and stakeholder engagement capabilities Good-to-Have Skills: Experience with Semantic Kernel or LangChain Working knowledge of AI Foundry for orchestrating AI pipelines Familiarity with Copilot extensibility and Teams App Studio Exposure to M365 Copilot APIs and custom plugin creation Knowledge of Responsible AI, data security, and compliance principles Familiarity with containerized deployment (Docker, Kubernetes) Experience in building dashboards and analytics (Kibana, Grafana) to visualize bot usage and performance Basic understanding of Power Platform (Power Automate, Power Apps) and its integration with AI
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