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

Vector Databases

- Pinecone

- ChromaDB

- FAISS

- Weaviate

- Milvus

📌 AI Engineer (Generative AI) (India)
🏢 Spait Infotech
📍 India