Junior Gen AI Developer (3 to 5 yrs)

LLM Implementation: Design and maintain applications powered by models like GPT-4, Claude, or Llama 3.

RAG Architecture: Develop and optimize Retrieval-Augmented Generation (RAG) pipelines to ensure AI responses are grounded in private data.

Prompt Engineering: Iterate on complex prompt templates and chains to improve accuracy, safety, and performance.

API Integration: Build robust APIs and microservices to connect AI capabilities with our core product.

Evaluation & Testing: Implement frameworks to evaluate LLM outputs (e.g., Ragas, TruLens) to mitigate hallucinations and ensure quality.

Vector Databases: Manage and query vector stores (e.g., Pinecone, Weaviate, or Milvus) for efficient document retrieval.

Languages: Expert proficiency in Python (most common) or TypeScript.

AI Frameworks: Deep experience with orchestration tools like LangChain, LlamaIndex, or Haystack.

Backend: Proficiency in web frameworks like FastAPI, Flask, or Django.

Data Science Basics: Understanding of embeddings, tokenization, and vector similarity search.

DevOps/Cloud: Experience deploying apps on AWS, Azure, or Google Cloud Platform, and familiarity with Docker.