AI Engineers

20 hours ago

uttar pradesh, India Recro Full time

Key Responsibilities Design 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.

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