Description

You will design, fine-tune, and deploy Generative AI systems and agentic workflows using Python and LLMs.

This role is hybrid.

Responsibilities

• Design and deploy AI models and agentic automation solutions using Python and AI libraries.
• Implement RAG systems utilizing vector databases like Pinecone or Milvus for knowledge-intensive automation.
• Preprocess data, perform feature engineering, and optimize model inference and scalability.
• Build self-improving automation using reinforcement learning and adaptive ML techniques.
• Ensure the security, scalability, and reliability of deployed models and automation workflows.

Required Skills

• 4+ years of experience in Python and Generative AI technologies including Hugging Face, LlamaIndex, and LangChain.
• 2+ years of experience in LLM fine-tuning, optimization, quantization, and prompt engineering.
• Proficiency with vector databases such as Pinecone, FAISS, or Milvus.
• Experience with cloud-based AI deployment using AWS SageMaker, Azure ML, or Vertex AI.
• Hands-on experience with REST APIs and cloud platforms including AWS, Azure, or GCP.
• Strong knowledge of AI agent architectures, workflow automation, and GPU-accelerated training/inference.
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

Preferred Skills

• Experience with front-end frameworks like Angular or React and back-end development with Node.js.
• Familiarity with microservices architecture and API-driven AI integration.
• Knowledge of embedding search, document scraping, and chunking for data retrieval.

Key Skills

Education

Bachelor's or Master's degrees