Description

You will design and implement AI-driven conversational agents and autonomous workflows for Tutor, Coach, and Buddy products.

This role is hybrid.

Responsibilities

• Build scalable pipelines for LLM interaction, Retrieval-Augmented Generation (RAG), and contextual memory.
• Integrate multi-modal capabilities (text, voice, image, video) into learning assistants.
• Develop evaluation frameworks for accuracy, relevance, safety, and personalization.
• Fine-tune and optimize prompt chains, embeddings, and tool-use logic.
• Research, test, and integrate new LLMs, APIs, and frameworks to enhance agent capabilities.

Required Skills

• 5+ years of hands-on experience building AI applications or agentic systems.
• Strong understanding of LLM architectures, embeddings, and RAG frameworks.
• Proficiency in Python and key AI/ML libraries including LangChain and LlamaIndex.
• Experience with OpenAI, Hugging Face, and vector databases like Pinecone or ChromaDB.
• Familiarity with API orchestration using FastAPI or Flask.
• Experience with database management systems such as MongoDB or PostgreSQL.
• Proficiency in Git/GitHub for version control.
• Knowledge of prompt engineering and system design for agents.
• Experience with AI evaluation metrics and safety considerations.

Preferred Skills

• Proficiency in TypeScript for full-stack integration.

Key Skills

Education

Any Graduate