AI Engineer

Job Summary:
We are seeking an experienced AI/ML Engineer with strong expertise in
Agentic AI/Multi-Agent Orchestration, a minimum of 2+ years of hands-on
experience in Natural Language Processing (NLP) and LLM (Large
Language Model)-based solutions. The ideal candidate should have a strong
background in Retrieval-Augmented Generation (RAG), vector database
design, chunking strategies, and chatbot development, along with proven
expertise in fine-tuning and integrating LLMs for real-world applications.

Key Responsibilities:
Design and develop NLP pipelines to process and extract insights from
unstructured data.
Build and optimize RAG (Retrieval-Augmented Generation) workflows for
LLM-based systems.
Implement chunking strategies to improve information retrieval and
response accuracy.
Work with vector databases (e.g., Pinecone, Weaviate, FAISS) to store
and retrieve embeddings efficiently.
Develop conversational AI/chatbot solutions using modern frameworks
and APIs.
Fine-tune, integrate, and deploy LLMs (Open-source or proprietary)
based on application needs.
Collaborate with product and engineering teams to translate business
requirements into intelligent AI-driven features.
Conduct experiments, evaluate model performance, and optimize
pipelines for scalability and accuracy.

Requirements:
2+ years of experience in AI/ML Engineering, Agentic AI, with a strong
focus on NLP & LLM.
Experience of FAST API is must
Proven experience with RAG frameworks, LLM fine-tuning, and prompt
engineering.Hands-on experience with vector databases such as FAISS, Pinecone,
Chroma, Weaviate, etc.
Strong understanding of embedding models, tokenization, and text
chunking techniques.
Experience in building chatbots and integrating with LLMs (OpenAI,
Cohere, HuggingFace, etc.).
Proficiency in Python and libraries like LangChain, Transformers,
PyTorch, or TensorFlow.
Knowledge of Cloud, Azure, MCP and agent based framework
Experience with deploying models using APIs, microservices, or
containerized solutions.

Nice to Have:
Knowledge of data privacy and security best practices in AI
systems. (Will be preferred)
Exposure to cloud services such as AWS, GCP, or Azure for AI/ML
workloads for deployment.
Django skills

Job Type: Full-time

Work Location: In person