GenAI Architect

7 days ago

San Francisco CA United States ZipRecruiter Full time

NAVA Software Solutions is looking for a Gen AI Architect

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 with Autogen and Azure AI Search is a MUST. This is not a document retrieval, summarization, or semantic search-based role.

Responsibilities:

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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/FastAPI development expertise with at least 2-3 projects 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+ years' experience leading the development of AI applications using Python backend frameworks and multiple inferencing pipelines.
  • Rapid PoC/Prototyping skills and expertise in building and demonstrating application blueprints without the need for a developer's assistance.
  • Deep, hands-on, and architectural proficiency in Python, AG-Grid, and ReactJS.
  • Hands-on expertise in SharePoint indexes and data/file structures (Azure SQL).
  • Good knowledge of Azure Form Recognizer for OCR of complex images, forms, and other data.
  • Hands-on with implementing TaskWeaver, Autogen, Agentic Flows, Retrieval Augmented (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 fine-tuning Azure OpenAI using MLOPS/LLMOPS pipelines.
  • Strong communication, architectural sketching, and collaboration skills.
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