Job Title: Generative AI Engineer Azure OpenAI & RAG Solutions

Job Summary

We are seeking a highly skilled Generative AI Engineer with strong expertise in Azure OpenAI, Retrieval-Augmented Generation (RAG), Prompt Engineering, and LLM Integration. The ideal candidate will be responsible for designing, developing, and optimizing enterprise-scale AI solutions using Large Language Models (LLMs), Azure AI services, and modern AI orchestration frameworks. This role requires hands-on experience in building production-ready GenAI applications, implementing evaluation frameworks, and integrating AI capabilities into business processes.

Key Responsibilities

LLM Implementation & Integration

- Design, develop, and implement core business logic and APIs using Python for integration with Azure OpenAI Service.
- Build scalable, secure, and high-performance Generative AI applications for enterprise use cases.
- Integrate LLM capabilities into existing platforms, applications, and business workflows.
- Collaborate with cross-functional teams to translate business requirements into AI-powered solutions.

RAG Architecture & Development

- Design and implement Retrieval-Augmented Generation (RAG) architectures using Azure services.
- Develop and optimize document ingestion, indexing, embedding, retrieval, and response-generation pipelines.
- Leverage Azure AI Search, vector databases, Azure Storage, and other Azure services to ground LLM responses with enterprise data.
- Improve retrieval quality, relevance, and overall solution performance through continuous optimization.

Prompt Engineering

- Create, test, and maintain sophisticated prompt strategies for conversational AI and other generative AI use cases.
- Develop dynamic prompting frameworks to improve response accuracy, contextual relevance, and user experience.




- Implement techniques to minimize hallucinations and enhance model reliability.
- Continuously refine prompts based on model performance and business feedback.

Model Evaluation & Optimization

- Define and implement evaluation frameworks, KPIs, and testing methodologies for GenAI applications.
- Monitor model accuracy, latency, response quality, and business outcomes.
- Conduct A/B testing and performance benchmarking of prompts, retrieval strategies, and AI models.
- Establish monitoring and governance mechanisms for production AI systems.

Required Skills & Qualifications

Technical Skills

- Expert proficiency in Python and API development.
- Strong experience with LLM orchestration frameworks such as LangChain, LlamaIndex, or similar.
- Deep practical experience with Azure OpenAI Service deployment, configuration, and management.
- Proven experience designing and implementing RAG architectures on Azure.
- Hands-on experience with:
- Azure AI Search
- Vector Databases
- Azure Storage Services
- Azure Functions / Web Apps / API Services

- Robust understanding of:

- Natural Language Processing (NLP)
- Semantic Search
- Embeddings
- Prompt Engineering
- LLM Fine-tuning concepts

- Experience with REST API development and cloud-native architectures.

Preferred Skills

- Experience with Azure AI Foundry, Azure Machine Learning, and AI governance frameworks.
- Knowledge of MLOps/LLMOps practices and CI/CD pipelines for AI solutions.
- Familiarity with model evaluation tools, observability, and monitoring frameworks.
- Experience working with enterprise-scale AI applications and data security requirements.

Educational Qualification

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

Experience

- 510 years of overall software development experience.
- Minimum 3+ years of hands-on experience in Generative AI, Azure OpenAI, or LLM-based application development.

📌 GEN AI Lead (Bengaluru)
🏢 ITC Infotech
📍 Bengaluru