Engineering Architect

3 weeks ago

Anywhere in IndiaMultiple Locations, IN Bonzer Business Solutions Pvt. Ltd. Full time

Job Description :


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 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.

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.

- Core Python - Iterators, Generators , OOP concepts, Python Shell (REPL) and Object Relational Mapper, Data structure and Exception handling etc.

- AI Search, Vector Database creation for relational databases and unstructured data.

- Azure app services expertise in terms of building and deploying AI apps using cloud services.

- 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 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.

- Hands on 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.

(ref:hirist.tech)

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