Software Developer
Summary
Build AI-powered Microsoft Teams bots using Python, M365 Agent SDK, and RAG with Azure AI Search to integrate LLMs into enterprise workflows.
Python Developer
We are currently looking to hire Python Developer .
This is an exciting opportunity to expand your skill set, achieve job satisfaction and work-life balance. More details as below Job Summary We are seeking a
skilled Python developer
to design, develop, and deploy
AI-powered Microsoft Teams Bot Applications
using the
Microsoft 365 Agent SDK . The role involves integrating
Large Language Models (LLMs)
with
Azure AI Search
(and other vector databases) to implement
Retrieval-Augmented Generation (RAG)
solutions. The ideal candidate will have a strong background in
Python, Microsoft Bot Framework, Azure AI services, and modern AI/ML techniques
to create intelligent, scalable, and user-friendly bot experiences. Key Responsibilities 1. M365Agent SDK & Bot Development Design, develop, and deploy
Microsoft Teams Bot Applications
using the
M365 Agent SDK
and
Python . Implement
conversational AI
workflows, including natural language understanding (NLU), dialog management, and multi-turn conversations. Integrate bots with
Microsoft Teams, Outlook, and other M365 services
using Microsoft Graph API. Optimize bot performance for
scalability, latency, and user experience . 2. AI &LLM Integration Develop and fine-tune
LLM-based solutions
(e.g., Azure Open AI, Hugging Face, or custom models) for conversational AI. Implement
prompt engineering
and
context management
to enhance bot responses. Integrate
Azure AI Search
(or other vector databases like Pinecone, Weaviate, or Chroma) for
semantic search and RAG . Design and optimize
embedding pipelines
for document retrieval and knowledge base augmentation. 3. RAG& Vector Database Implementation Build
Retrieval-Augmented Generation (RAG)
systems to ground LLM responses in enterprise data. Index, chunk, and embed
unstructured data
(PDFs, documents, emails) for efficient retrieval. Evaluate and compare
vector databases
(Azure AI Search, Pinecone, Weaviate, etc.) for performance, cost, and scalability. Implement
hybrid search
(keyword + vector) for improved accuracy. 4. Cloud& DevOps Deploy and manage
Azure resources
(App Services, Container Instances, etc.) for bot hosting. Implement/modify
CI/CD pipelines
for automated testing and deployment. Ensure
security best practices
(authentication, authorization, data encryption) for bot and AI services. 5.Collaboration & Documentation Work closely with
cross-functional teams
(product managers, UX designers, data scientists) to refine bot capabilities. Document
APIs, workflows, and system design
for internal knowledge sharing. Provide
training and support
to end-users and stakeholders.
This is an exciting opportunity to expand your skill set, achieve job satisfaction and work-life balance. More details as below Job Summary We are seeking a
skilled Python developer
to design, develop, and deploy
AI-powered Microsoft Teams Bot Applications
using the
Microsoft 365 Agent SDK . The role involves integrating
Large Language Models (LLMs)
with
Azure AI Search
(and other vector databases) to implement
Retrieval-Augmented Generation (RAG)
solutions. The ideal candidate will have a strong background in
Python, Microsoft Bot Framework, Azure AI services, and modern AI/ML techniques
to create intelligent, scalable, and user-friendly bot experiences. Key Responsibilities 1. M365Agent SDK & Bot Development Design, develop, and deploy
Microsoft Teams Bot Applications
using the
M365 Agent SDK
and
Python . Implement
conversational AI
workflows, including natural language understanding (NLU), dialog management, and multi-turn conversations. Integrate bots with
Microsoft Teams, Outlook, and other M365 services
using Microsoft Graph API. Optimize bot performance for
scalability, latency, and user experience . 2. AI &LLM Integration Develop and fine-tune
LLM-based solutions
(e.g., Azure Open AI, Hugging Face, or custom models) for conversational AI. Implement
prompt engineering
and
context management
to enhance bot responses. Integrate
Azure AI Search
(or other vector databases like Pinecone, Weaviate, or Chroma) for
semantic search and RAG . Design and optimize
embedding pipelines
for document retrieval and knowledge base augmentation. 3. RAG& Vector Database Implementation Build
Retrieval-Augmented Generation (RAG)
systems to ground LLM responses in enterprise data. Index, chunk, and embed
unstructured data
(PDFs, documents, emails) for efficient retrieval. Evaluate and compare
vector databases
(Azure AI Search, Pinecone, Weaviate, etc.) for performance, cost, and scalability. Implement
hybrid search
(keyword + vector) for improved accuracy. 4. Cloud& DevOps Deploy and manage
Azure resources
(App Services, Container Instances, etc.) for bot hosting. Implement/modify
CI/CD pipelines
for automated testing and deployment. Ensure
security best practices
(authentication, authorization, data encryption) for bot and AI services. 5.Collaboration & Documentation Work closely with
cross-functional teams
(product managers, UX designers, data scientists) to refine bot capabilities. Document
APIs, workflows, and system design
for internal knowledge sharing. Provide
training and support
to end-users and stakeholders.