GenAI Developer

This is a permanent work from home position from anywhere in India

Notice period - less than 30 Days (Immediate joiners preferred)

Job Description:

We are looking for a talented GenAI Developer with a strong background in developing rule-based AI solutions using Azure AI, GPT-3.5, and GPT-4. The ideal candidate will have experience working with Azure SQL, document flow logic in Azure AI specifically RAG (Retrieval-Augmented Generation), and expertise in prompt engineering and entity query concepts. A solid understanding of CI/CD, GitHub, Python, and DevOps environments is required, with experience in Langchain being a bonus.


Key Responsibilities:

Azure AI & GPT Development: Build and maintain AI solutions using Azure AI with GPT-3.5 and GPT-4, including rule-based and context-driven models.
Document Flow & RAG: Develop solutions that handle complex document flow logic using Azure AIs Retrieval-Augmented Generation (RAG) for intelligent document retrieval and processing.
Prompt Engineering: Design and implement effective prompt logic, output sanitization, and filtering to optimize the performance of AI-generated outputs.
Query Logic & Entity Recognition: Implement query logic with a focus on entity recognition and handling complex query structures to return accurate and relevant information.
LLM Structure: Work with Large Language Models (LLMs), understanding their structure and integration into scalable AI solutions.
CI/CD & DevOps: Collaborate in a CI/CD environment using GitHub and DevOps practices to ensure efficient code deployment and project continuity.
Python Development: Use Python for scripting, automation, and development of AI-based applications.
Langchain Integration: (Optional) Experience with Langchain to manage LLM application development.

Required Skills and Experience:

AI Development: Experience with GPT-3.5 and GPT-4 in Azure AI, including rule-based and retrieval-augmented generation.
Azure SQL: Proficiency in Azure SQL and handling data flows between the AI models and databases.
RAG Logic: Deep understanding of Retrieval-Augmented Generation (RAG) and document flow within AI systems.
Prompt Engineering: Expertise in prompt logic, output sanitization, and entity-based query logic for efficient AI response generation.
LLM Knowledge: Strong knowledge of Large Language Models (LLMs) and how they integrate with AI-driven solutions.
CI/CD & DevOps: Experience working in CI/CD environments, using tools like GitHub and Azure DevOps for continuous integration and delivery.
Programming: Proficient in Python for AI model development and scripting tasks.

Preferred Qualifications:

Experience with Langchain for LLM-based application development.
Familiarity with Azure Cognitive Services and Machine Learning frameworks.
Understanding of data security and AI ethics related to generative models.
Role: Back End Developer