Job Description:As a GenAI Engineer / Sr. GenAI Engineer, you will lead the design, development, and deployment of production-grade AI solutions. You aren't just building prototypes; you are architecting scalable RAG systems, fine-tuning models for specific domain expertise, and ensuring that GenAI capabilities integrate seamlessly into enterprise-level applications.Key Responsibilities:LLM Orchestration:- Design and deploy sophisticated LLM-based applications using frameworks such as LangChain, LlamaIndex, or Semantic Kernel.Model Optimization:- Lead the fine-tuning of open-source and proprietary models to improve performance, latency, and cost-efficiency.Advanced RAG Systems:- Architect and optimize Retrieval-Augmented Generation (RAG) pipelines utilizing vector databases like Pinecone, FAISS, Weaviate, or Azure AI Search.Scalable Deployment:- Containerize services using Docker and deploy via FastAPI and Azure Functions to ensure high availability and low latency.Productization:- Build and scale enterprise-grade chatbots, copilots, and automated content generation tools using OpenAI/Azure OpenAI and Hugging Face.Prompt Engineering:- Implement and manage advanced prompt optimization and versioning workflows to enhance model accuracy.Monitoring & Evaluation:- Establish robust evaluation frameworks (e.g., RAGAS, TruLens) to track model performance, hallucination rates,



and drift in production.Operationalization:- Collaborate with cross-functional teams (Product, DevOps, Data) to identify high-impact use cases and move them from POC to production.Best Practices:- Set the standard for GenAI engineering, including model selection criteria, performance tracking, and ethical AI safeguards.Required Skills & Qualifications:Overall Experience:- 3 to 6 years of qualified software engineering experience.GenAI Domain Experience:- 2 years of dedicated, hands-on experience building GenAI, LLM, and OCR solutions in production environments.Programming Mastery:- Deep proficiency in Python with expertise in asynchronous programming, typing standards, and clean code principles.Generative AI & LLMs:- Hands-on experience with commercial APIs (OpenAI GPT-4o, Anthropic Claude, Azure OpenAI) and open-source models (Llama 3, Mistral), along with modern agentic frameworks.Vector Infrastructure & Search:- Practical experience with hybrid search (dense + sparse), re-ranking algorithms, metadata filtering, and vector index tuning.Backend & Cloud:- Strong background in FastAPI, Docker, Git, CI/CD pipelines, and enterprise cloud ecosystems (Azure / AWS).Problem Solving:- Proven track record of solving hallucination, context window limitations, and data grounding issues in production. (ref:hirist.tech)

📌 Senior GenAI Engineer - LLM/RAG (India)
🏢 Resource tree Global Services
📍 India