GenAI Engineer: Azure OpenAI, RAG Pipelines & Prompts

Quality Ai; Center (TX); On-site; USD 15,585 - 29,092; Full time

Job summary

QualityAI in India seeks a GenAI Developer to design and implement GenAI‑powered solutions using LLMs and RAG architectures. You will build ingestion pipelines, prompts, and AI workflows, integrating Azure OpenAI, embeddings, and vector databases. Collaborate with architects and business teams to deliver reliable AI solutions.

Responsibilities include designing prompts, tuning models, and ensuring governance and responsible AI considerations throughout the project lifecycle.

Qualifications

• Experience with Azure OpenAI, OpenAI, LangChain, Semantic Kernel, or similar frameworks.
• Strong Python development skills.
• Knowledge of RAG, vector databases, embeddings, and prompt engineering.
• Familiarity with Azure AI Search and enterprise AI architectures.
• Understanding of responsible AI and governance principles.

Responsibilities

• Develop and implement GenAI‑powered solutions using LLMs and RAG architectures.
• Build document ingestion, chunking, metadata extraction, and retrieval pipelines.
• Design and optimize prompts, workflows, and AI orchestration logic.
• Integrate Azure OpenAI, vector databases, and search services.
• Implement hybrid search, semantic retrieval, and response generation capabilities.
• Evaluate and improve model accuracy, relevance, and performance.
• Develop agentic workflows and AI automation components.
• Conduct prompt tuning, testing, and model validation.
• Collaborate with architects, API developers, and business teams.
• Document AI solution design, configurations, and best practices.

Skills

Azure OpenAI

OpenAI

LangChain

Semantic Kernel

RAG

Vector DB

Prompt engineering

Python

Azure AI Search

Enterprise AI Arch

Responsible AI

Governance

Job description

QualityAI in India seeks a GenAI Developer to design and implement GenAI‑powered solutions using LLMs and RAG architectures. You will build ingestion pipelines, prompts, and AI workflows, integrating Azure OpenAI, embeddings, and vector databases. Collaborate with architects and business teams to deliver reliable AI solutions.

Responsibilities include designing prompts, tuning models, and ensuring governance and responsible AI considerations throughout the project lifecycle.