AI Python Developer (Experience in Flask, AWS Bedrock, Dynamo DB, PostgreSQL)
Budget: ₹75,000 – ₹150,000 INR
Techyons is an AI-powered SaaS platform for B2B MSMEs that brings projects, meetings, chat, and AI Drafts together in one secure workspace. AI Drafts is our first-of-its-kind tool that turns context into ready documents (BRDs, briefs, reports, etc.). Unlike siloed tools like Trello or Zoom, Techyons Platform is connected through an AI layer that keeps context across workflows - no switching apps, no lost context.
Website: https://techyons.io/
Techyons is seeking an expert developer to work on AI Drafts, a solution for automating requirement documents using a Retrieval-Augmented Generation (RAG) approach. The project involves leveraging AWS Bedrock Agents and Pinecone knowledge bases to streamline the creation of Business Requirement Documents, System Requirement Specifications, and Change Requests. The goal is to reduce repetition and inconsistencies in document drafting.
A ready-to-deploy MVP is already built. Demo available on the website. Below are the deliverables.
Deliverables
Validate and optimise the RAG architecture, including the integration of Bedrock and
Pinecone.
Provide guidance on prompt engineering and metadata filtering techniques.
Enhance the design of the knowledge base to ensure scalability and accuracy.
Prototype integrations with Techyons’ broader platform ecosystem.
Ensure compliance and auditability across all generated documents.
Extending use-cases to legal professionals, digital marketing agencies etc.
Interested candidates can reply on info@thetechyon(dot)io. Thanks.
Website: https://techyons.io/
Techyons is seeking an expert developer to work on AI Drafts, a solution for automating requirement documents using a Retrieval-Augmented Generation (RAG) approach. The project involves leveraging AWS Bedrock Agents and Pinecone knowledge bases to streamline the creation of Business Requirement Documents, System Requirement Specifications, and Change Requests. The goal is to reduce repetition and inconsistencies in document drafting.
A ready-to-deploy MVP is already built. Demo available on the website. Below are the deliverables.
Deliverables
Validate and optimise the RAG architecture, including the integration of Bedrock and
Pinecone.
Provide guidance on prompt engineering and metadata filtering techniques.
Enhance the design of the knowledge base to ensure scalability and accuracy.
Prototype integrations with Techyons’ broader platform ecosystem.
Ensure compliance and auditability across all generated documents.
Extending use-cases to legal professionals, digital marketing agencies etc.
Interested candidates can reply on info@thetechyon(dot)io. Thanks.
Related categories:
Software Architecture
PostgreSQL
Flask
Prompt Engineering
AI Development
Agentic AI