Matrimony com
AI Engineer / NLP, LLM & Agentic AI Specialist (Python)
- Compensation
- Not disclosed
- Location
- Chennai
- Work setup
- Onsite
- Seniority
- Middle
- Employment
- Full time
- Experience
- Not specified
- Category
- Ai engineering
- Posted
Skills
Must have
- Proficient in Python and NLP libraries (SpaCy, Transformers, NLTK, Gensim).
- Hands-on experience with LLM APIs and prompt-driven application development.
- Strong understanding of agentic AI concepts (planning, memory, tool use, multi-step reasoning).
- Experience with Hugging Face Transformers for training/fine-tuning.
- Knowledge of NLP fundamentals: embeddings, attention, tokenization.
- Familiarity with vector databases like FAISS, Weaviate, or Pinecone (RAG systems).
- Experience building REST APIs and working with Docker and Git.
Full description
Job Title: AI Engineer / NLP, LLM & Agentic AI Specialist (Python)
Location: Chennai
Experience Level: Mid-Level / Senior
Employment Type: Full-Time
Job Summary
We are looking for a passionate AI Engineer with strong expertise in Python, Natural Language Processing (NLP), Large Language Models (LLMs), and emerging Agentic AI systems. You will design and build intelligent, autonomous language-based solutions, integrate LLM APIs, and develop AI agents capable of reasoning, planning, and executing multi-step tasks in real-world applications.
Key ResponsibilitiesModel Development, NLP & Agentic Systems
- Design and build NLP pipelines for tasks like classification, NER, summarization, sentiment analysis, and Q&A.
- Fine-tune and optimize open-source LLMs (e.g., BERT, GPT, T5) using Hugging Face Transformers.
- Develop agentic AI workflows that enable autonomous decision-making, multi-step reasoning, and tool usage.
- Build and orchestrate AI agents capable of interacting with APIs, databases, and external tools.
- Preprocess and structure large-scale textual datasets using SpaCy, NLTK, or custom tokenizers.
LLM Integration, Prompt Engineering & Agents
- Integrate LLM APIs (OpenAI, Claude, Cohere, Hugging Face) into real-time applications.
- Design, develop, and optimize prompt strategies and agent behaviors for reliability and performance.
- Build intelligent agents for use cases like chatbots, copilots, recommendation systems, and automation workflows.
- Implement tool-augmented agents and function-calling pipelines.
- Collaborate with product teams to embed LLMs and agentic systems into user-facing applications.
Deployment & Continuous Improvement
- Deploy models and agent systems as APIs using Flask, FastAPI, or Streamlit; containerize with Docker.
- Monitor model and agent performance, including reasoning accuracy and task completion rates.
- Implement evaluation pipelines for LLM and agent outputs.
- Continuously improve systems using user feedback and performance metrics.
- Stay updated with advancements in GenAI, agent frameworks, and NLP research.
Required Skills & Experience
- Proficient in Python and NLP libraries (SpaCy, Transformers, NLTK, Gensim).
- Hands-on experience with LLM APIs and prompt-driven application development.
- Strong understanding of agentic AI concepts (planning, memory, tool use, multi-step reasoning).
- Experience with Hugging Face Transformers for training/fine-tuning.