GenAI Architect
GenAI Architect
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1 Vacancy
Job Description
NAVA Software solutions is looking for a Gen AI Architect
Details:
GenAI Architect (Must have AutogenCrewAI and WrenAI)
Location: San Francisco CA Hybrid
Duration: 12 months
This role requires handson project expertise to implement an enterprise application built on top of SQL and unstructured data (imagesvideoslogs etc.) using Autogen CrewAI Azure OpenAI GPT4 Turbo and GPT4V with PTUs. This is a handson architect role requiring both deep technical skills and the ability to deliver complex AI applications endtoend on large operational databases to render charts tables and other insights as completions from NLPbased prompts. Deep experience of Autogen and Azure AI Search is a MUST. This is not a document retrieval summarization or semantic searchbased role.
Responsibilities:
- Architectural Design:
- Collaborate with stakeholders to understand business requirements and translate them into architectural blueprints.
- Design scalable secure and highperformance architecture for the Autogenbased LLMIntegrated 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 AGGrid Flask / Django / Fast API development expertise with least 23 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 SearchVector Database creation for relational databses 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.
- 910 years of overall technology experience in core application development AI project architectural leadership of at least 3 years
- 5 years 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 developers assistance.
- Deep handson and architectural proficiency in PythonAgGrid and ReactJS
- Handson 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 PineconeFAISSWeaviate or ChromaDB
- Deep expertise in Prompt Engineering using DsPy tools etc.
- Knowledge of NLP techniques like transformer networks embeddings intent recognition etc.
- Handson skills on Embedding and finetuning Azure OpenAI using MLOPS/LLMOPS pipelines.
- Strong communication architectural sketching and collaboration skills
Employment Type
Full Time
