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 - 7 years - Immediate Joiners (Bengaluru)
🏢 ResourceTree Global Services
📍 Bengaluru