Gen AI Architect

About

NAVA Software solutions is looking for a Gen AI Architect

Role Details

GenAI Architect (Must have - Autogen,CrewAI and WrenAI)

Location: San Francisco CA - Hybrid

Duration: 12 months

This role requires hands-on project expertise to implement an enterprise application built on top of SQL and unstructured data (images,videos,logs etc.) using Autogen, CrewAI, Azure OpenAI GPT-4 Turbo and GPT-4V with PTUs. This is a hands-on architect role requiring both deep technical skills and the ability to deliver complex AI applications end-to-end on large operational databases to render charts, tables and other insights as completions from NLP-based prompts. Deep experience of Autogen and Azure AI Search is a MUST. This is not a document retrieval, summarization or semantic search-based role.

Responsibilities

Architectural Design

• Collaborate with stakeholders to understand business requirements and translate them into architectural blueprints.
• Design scalable, secure, and high-performance architecture for the Autogen-based LLM-Integrated application.
• Define data models and schemas for integrating operational data from relational databases into the application.

Implementation and Development

• Lead the implementation efforts, ensuring adherence to architectural guidelines and best practices.
• Develop robust APIs and interfaces for seamless communication between the application and relational databases.
• Write efficient and maintainable code, following coding standards and version control processes.

Integration and Testing

• Integrate operational data from various relational databases into the application, ensuring data consistency and integrity.
• Conduct thorough testing, including unit testing, integration testing, and performance testing, to validate the functionality and scalability of the application.
• Troubleshoot and debug issues as they arise during the integration and testing phases.

Optimization and Performance Tuning

• Identify performance bottlenecks and optimization opportunities within the application architecture.
• Implement performance tuning strategies to improve the speed, reliability, and efficiency of data retrieval and processing.
• Continuously monitor system performance and proactively address any degradation or inefficiencies.

Documentation and Knowledge Sharing

• Create comprehensive technical documentation, including architecture diagrams, API specifications, and deployment procedures.
• Conduct knowledge sharing sessions to disseminate architectural knowledge and best practices among team members.
• Provide guidance and mentorship to junior team members, fostering their professional growth and development.

Requirements

• Must have : Autogen Framework, CrewAI, WrenAi, SQL Agents, AG-Grid Flask / Django / Fast API development expertise with least 2-3 project delivered as a lead developer / implementation architect.
• Must have : Core Python - Iterators, Generators , OOP concepts, Python Shell (REPL) and Object Relational Mapper, Data structure and Exception handling etc.
• Must have : AI Search,Vector Database creation for relational databases and unstructured data
• Must have : Azure app services expertise in terms of building and deploying AI apps using cloud services.
• Must have : Deep expertise in Azure SQL, Azure Data Factory , Linked Services and Azure Synapse etc.
• 9-10 years of overall technology experience in core application development + AI project architectural leadership of at least 3 years
• 5+ year's experience leading development of AI application using Python backend frameworks and multiple inferencing pipelines
• Rapid PoC/Prototyping skills and expertise in building and demonstrating application blueprints without need a developer's assistance.
• Deep, hands-on and architectural proficiency in Python,Ag-Grid and ReactJS
• Hands-on expertise of SharePoint indexes and data/file structures (Azure SQL)
• Good knowledge of Azure Form Recognizer for OCR of complex images, forms and other data
• Handson with implementing TaskWeaver, Autogen, Agentic Flows, Retrieval Augmented Generation (RAG) and RLHF (Reinforcement Learning from Human Feedback)
• Designing and implementing vector databases on Azure cloud using Ai Search and Cosmos DB vCore
• Sound project implementation level knowledge of Pinecone,FAISS,Weaviate or ChromaDB
• Deep expertise in Prompt Engineering using DsPy tools etc.
• Knowledge of NLP techniques like transformer networks, embeddings, intent recognition etc.
• Hands-on skills on Embedding and finetuning Azure OpenAI using MLOPS/LLMOPS pipelines.
• Strong communication, architectural sketching, and collaboration skills