Engineering Architect- Gen Ai

5 days ago

Delhi, India Bonzer Business Solutions Pvt. Ltd. Full time
GenAI Engineering Architect (Must have - AutoGen, CrewAI and WrenAI)This role requires hands-on project expertise to implement an enterprise application built on top of SQLand unstructured data (images,videos,logs etc.) using AutoGen, CrewAI, Azure OpenAI GPT-4 Turbo andGPT-4V with PTUs. This is a hands-on architect role requiring both deep technical skills and the ability todeliver complex AI applications end-to-end on large operational databases to render charts, tables andother insights as completions from NLP-based prompts. Deep experience of Autogen and Azure AI Searchis 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 theminto 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 relationaldatabases into the application.2. Implementation and Development:
- Lead the implementation efforts, ensuring adherence to architectural guidelines and bestpractices.
- Develop robust APIs and interfaces for seamless communication between the applicationand relational databases.
- Write efficient and maintainable code, following coding standards and version controlprocesses.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 performancetesting, 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 applicationarchitecture.
- Implement performance tuning strategies to improve the speed, reliability, and efficiencyof data retrieval and processing.
- Continuously monitor system performance and proactively address any degradation orinefficiencies.5. Documentation and Knowledge Sharing:
- Create comprehensive technical documentation, including architecture diagrams, APIspecifications, and deployment procedures.
- Conduct knowledge sharing sessions to disseminate architectural knowledge and bestpractices among team members.
- Provide guidance and mentorship to junior team members, fostering their professionalgrowth and development.Requirements:
- Must have : AutoGen Framework, CrewAI, WrenAI, SQL Agents, AG-Grid Flask / Django / Fast APIdevelopment expertise with least 2-3 project delivered as a lead developer / implementationarchitect.
- Must have : Core Python – Iterators, Generators, OOP concepts, Python Shell (REPL) and ObjectRelational 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 cloudservices.
- Must have : Deep expertise in Azure SQL, Azure Data Factory, Linked Services and Azure Synapseetc.
- 9-10 years of overall technology experience in core application development + AI projectarchitectural leadership of at least 3 years
- 5+ years’ experience leading development of AI application using Python backend frameworksand multiple inferencing pipelines
- Rapid PoC/Prototyping skills and expertise in building and demonstrating application blueprintswithout 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 AugmentedGeneration (RAG) and RLHF (Reinforcement Learning from Human Feedback)
- Designing and implementing vector databases on Azure cloud using Ai Search and Cosmos DBvCore
- 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

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