Job Title

Key ResponsibilitiesDesign and implement AI-driven conversational agents and autonomous workflows across Tutor, Coach, and Buddy products. Build scalable pipelines for LLM interaction, retrieval-augmented generation (RAG), and contextual memory.- Integrate multi-modal capabilities (text, voice, image, video) into learning assistants. - Collaborate with product, data, and backend teams to align agent behavior with learning outcomes and UX. - Develop evaluation frameworks for accuracy, relevance, safety, and personalization. - Fine-tune and optimize prompt chains, embeddings, and tool-use logic. - Ensure compliance with ethical AI practices, hallucination reduction, and content moderation. - Continuously research, test, and integrate new LLMs, APIs, and frameworks to enhance agent capabilities. - Contribute to building reusable AI components and internal SDKs for faster agent development. - Support A/B testing, telemetry integration, and performance analytics for deployed agents.Required Skills & Qualifications- Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or a related field. - 1–3 years of hands-on experience building AI applications, chatbots, or agentic systems. - Strong understanding of LLM architectures, embeddings, vector databases, and RAG frameworks. - Proficiency in Python and key AI/ML libraries (LangChain, LlamaIndex, OpenAI, Hugging Face). - Experience with API integration, orchestration (FastAPI/Flask), and database management (MongoDB/Postgres). - Familiarity with prompt engineering, system design for agents, and evaluation metrics. - Excellent problem-solving, debugging, and documentation skills. - Curiosity to explore emerging AI models, frameworks, and autonomous system designs. - Tooling Proficiency (Must/Strongly Preferred) - Frameworks: LangChain, LlamaIndex, OpenAI API, Hugging Face Transformers - Programming: Python, TypeScript (nice to have) - Databases: Pinecone, ChromaDB, FAISS, PostgreSQL - APIs & Deployment: FastAPI, Flask, Docker - Version Control: Git/GitHub - Evaluation & Monitoring: Weights & Biases, PromptLayer, LangFuse - Cloud & CI/CD: AWS, GCP, or Azure (preferred); GitHub Actions, Jenkins (nice to have)Bonus Points- Experience in building educational or learning-focused AI systems. - Understanding of pedagogy, personalization models, and adaptive learning. - Familiarity with voice agents, speech-to-text, and emotion detection APIs. - Knowledge of graph-based memory or multi-agent frameworks. - Experience conducting AI safety, fairness, and reliability evaluations.WhatWe Offer- Opportunity to shape the core AI systems of a fast-scaling EdTech company. - Collaborative, research-driven, and mission-focused environment. - Competitive compensation, ownership, and career growth opportunities. - Flexible work setup and a chance to impact millions of learners globally.