Description

You will design, develop, and deploy enterprise-grade AI applications using Large Language Models, RAG, and Agentic AI frameworks. This role focuses on building production-ready systems with modern MLOps/LLMOps practices.

This role is hybrid.

Responsibilities

• Design and develop LLM-powered AI applications and RAG solutions.
• Build AI services using LangChain, LlamaIndex, Hugging Face, and vector databases.
• Fine-tune and optimize LLMs using LoRA, PEFT, and related techniques.
• Develop scalable APIs and microservices for AI applications.
• Deploy AI solutions using Kubernetes, CI/CD, and cloud platforms while monitoring performance, latency, and cost.

Required Skills

• 7+ years of AI/ML or Software Engineering experience.
• Strong experience building and deploying production-grade LLM/GenAI applications.
• Proficiency in Python, PyTorch, or TensorFlow.
• Deep understanding of Large Language Models, Generative AI, and Retrieval-Augmented Generation (RAG).
• Experience with Agentic AI architectures.
• Hands-on experience with LangChain, LlamaIndex, and Hugging Face.
• Knowledge of Embeddings, Vector Databases, and Model Evaluation & Observability.
• Experience deploying via Kubernetes, CI/CD, and building APIs/Microservices.
• Familiarity with MLOps/LLMOps and AI security/privacy best practices.

Preferred Skills

• Experience with full-stack AI engineering.
• Strong problem-solving and communication skills for cross-team collaboration.

Key Skills

Education

Not specified