Description

You will design, build, and deploy scalable LLM-powered applications and AI-driven products.

This role is on-site.

Responsibilities

• Build AI agents and Agentic AI systems capable of reasoning, planning, and executing complex workflows.
• Develop Retrieval-Augmented Generation (RAG) pipelines leveraging proprietary enterprise knowledge bases.
• Design and implement MCP servers, AI assistants, and multi-modal AI platforms.
• Integrate AI/ML solutions with enterprise systems, APIs, cloud platforms, and data ecosystems.
• Build MLOps and LLMOps pipelines for monitoring, governance, evaluation, and continuous improvement.

Required Skills

• 5+ years of hands-on experience building and deploying production-grade AI applications.
• Proficiency in Python Programming and API Development.
• Deep understanding of Large Language Models (LLMs), Generative AI, and Agentic AI.
• Experience with LangChain, LangGraph, and Hugging Face.
• Solid grasp of Retrieval-Augmented Generation (RAG), Prompt Engineering, and Embeddings.
• Knowledge of Vector Databases and Model Evaluation techniques.
• Experience with AI tools such as Claude Code, Codex, Cursor, or GitHub Copilot.
• Ability to optimize LLM performance through orchestration, fine-tuning, and prompt engineering.

Preferred Skills

• Experience with AWS, Azure, or GCP Cloud Platforms and Snowflake.
• Familiarity with LlamaIndex, AutoGen, CrewAI, or Semantic Kernel.
• Knowledge of Fine-Tuning LLMs (LoRA, PEFT), MLOps/LLMOps, and AI Governance.

Qualifications

Bachelor’s or Master’s Degree in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, or a related field.

Key Skills

Education

Bachelor's or Master's degrees