Key Responsibilities
Design, develop, and deploy AI-powered applications using GPT and Large Language Models (LLMs).
Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and embedding models.
Develop AI-based resume matching systems to intelligently match candidates with job descriptions.
Integrate Voice AI capabilities, including speech-to-text, text-to-speech, and conversational AI solutions.
Design and implement personalized recommendation engines using machine learning and AI techniques.
Create, optimize, and evaluate prompts for LLMs to improve response quality and accuracy.
Fine-tune AI models and optimize inference performance.
Develop scalable REST APIs and microservices for AI applications.
Work closely with product managers, data scientists, and software engineers to deliver AI-driven features.
Monitor model performance, troubleshoot issues, and continuously improve AI solutions.
Stay up to date with the latest advancements in Generative AI,
LLMs, and emerging AI technologies.
Required Skills
Generative AI
GPT Integration (OpenAI, Azure OpenAI, Claude, Gemini, or similar)
Prompt Engineering
Retrieval-Augmented Generation (RAG)
LLM Application Development
AI Agents and Multi-Agent Systems (preferred)
Machine Learning & AI
Resume Matching Algorithms
Recommendation Systems
Natural Language Processing (NLP)
Semantic Search
Embeddings and Vector Search
Voice AI
Speech-to-Text (STT)
Text-to-Speech (TTS)
Conversational AI
Voice Bot Development
Programming
Python (Mandatory)
FastAPI or Flask
REST APIs
SQL and NoSQL Databases
AI Frameworks
LangChain
LlamaIndex
Hugging Face Transformers
PyTorch or TensorFlow