Senior GenAI Developer
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Below is a breakdown of the skills set needed to successfully build, deploy, and maintain an enterprise level RAG application in Azure.
Cloud Infrastructure & DevOps
- Azure Cloud Expertise: Understanding of Azure services such as Azure OpenAI, CosmosDB, Azure Search, Azure Functions, Key Vault, and Azure Storage.
Skills: Azure CLI, Azure DevOps, Terraform for infrastructure as code, managing Azure Resource Groups, App Services, and Azure Function Apps.
- Infrastructure as Code (IaC):
Skills: Terraform, Makefile scripting, handling Azure resource provider registration.
- CI/CD Pipeline Setup and Maintenance: Ability to set up and maintain continuous integration and deployment pipelines (e.g., using Azure DevOps or GitHub Actions).
Skills: Azure DevOps Pipelines, GitHub Codespaces, GitHub Actions, Docker/Containers.
- Containerization: Managing containers in Azure, including using development containers in GitHub Codespaces.
Skills: Docker, container orchestration tools, Azure Kubernetes Service (AKS).
- Security and Compliance: Managing security for Azure AD, handling authentication and authorization, managing secrets via Key Vault, DDoS protection, and securing the environment.
Skills: Azure AD, OAuth, managing roles and permissions, security best practices, network security (private vnets, etc.).
Backend Development
- Python Backend Development: The core backend services are written in Python
Skills: Python, Flask, API development, integration with Azure services like Azure AI Search, Azure Storage, CosmosDB.
- RAG Application Knowledge: Experience in building applications that use RAG to retrieve information and augment responses using models such as GPT and embedding models.
Skills: Azure OpenAI models (gpt-4o, text-embedding-ada-002), prompt engineering, embedding APIs, text chunking and indexing for AI-driven search.
- Data Processing Pipelines: Creating and managing document processing pipelines for language translation, embedding text chunks, etc.
Skills: Python-based task orchestration, Azure Functions for event-driven architecture.
- Database Management: Knowledge of Azure CosmosDB for document storage and hybrid search indexes.
Skills: NoSQL databases, CosmosDB, SQL, indexing/search techniques.
Frontend Development
- React and Typescript Development: The frontend is built using React and Typescript, along with Vite for compiling the app.
Skills: React, Typescript, Vite, modern front-end frameworks, and front-end optimization.
- Web Integration with Backend APIs: Ensuring smooth communication between the Python-based backend APIs and the Typescript frontend.
Skills: API integration (REST), state management in React (e.g., Redux or context API).
- Web Security: Securing the frontend application, especially considering integration with Azure AD for user authentication.
Skills: OAuth, JWT, authentication mechanisms using Azure AD.
AI Engineering
- Handling Data for AI Models: Expertise in managing and processing data for use with AI models, including managing large text datasets, embeddings, and hybrid indexing.
Skills: Text embeddings, vector databases, knowledge of AI models for search (sentence transformers, OpenAI models).
- LLM Integration & Fine-tuning: Fine-tuning or configuring models like GPT for specific tasks within the Azure ecosystem.
Skills: Azure OpenAI models, language model fine-tuning, embedding generation, hybrid search integration.