Job Description
As a Gen AI Engineer / Sr. Gen AI 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 skilled 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.

📌 Senior Gen AI Engineer (Bengaluru)
🏢 ResourceTree Global Services
📍 Bengaluru