📌 Job Title : Senior AI Engineer – GenAI Systems & AI Agent Architecture
📍 Location : Noida / Hybrid
🕒 Type : Full-time
💰 Compensation : Competitive – based on experience (CTC + ESOP options)
🚀 About YoLearn.ai
YoLearn.ai is building the world’s most emotionally intelligent, personalized learning OS — powered by AI tutors, coaches, and study buddies. Our platform blends deep pedagogical thinking with cutting-edge GenAI, LLMs, and agentic architectures to transform how students learn and how teachers teach.
We're looking for a Senior AI Engineer with a strong foundation in machine learning , LLMs , and AI agent infrastructure — who has built real AI apps , not just played with notebooks. You’ll work closely with the founder, AI research engineers, backend devs, and product teams to power everything from tutoring agents to live multimodal avatars.
🎯 Responsibilities🧠 AI & ML System Development
- Architect, train, fine-tune, and deploy models (ML + DL + LLMs)
- Build and scale GenAI applications : RAG systems, recommender engines, forecasting models
- Engineer robust AI agents with memory, personalization, tool access, and reasoning logic
- Handle multi-agent orchestration , streaming audio / video interfaces , and real-time AI flows
🧰 Engineering & Infra
Design and optimize data pipelines : cleaning, preprocessing, feature engineeringBuild production APIs (FastAPI preferred) for AI tools and core platform functionality (billing, notifications, usage logs, profiles, history)Manage CI / CD pipelines , containers (Docker), orchestration (Kubernetes), and deployment workflowsIntegrate with AWS services : Sagemaker, Bedrock, Lambda, EC2, ECS / EKS, Redis, S3, Athena, Step Functions , etc.Work on LLM fine-tuning , retrieval augmentation, and model context protocols (MCP)🤖 GenAI & LangChain Ecosystem
Build GenAI tools using OpenAI, LLaMA, DeepSeek, Mistral , etc.Use LangChain , LLM orchestration frameworks , and vector DBs (Qdrant, FAISS, Weaviate, pgvector)Construct RAG-based assistants , multi-turn memory, agent-based logic📊 AI Product Features
NLP tasks (NER, summarization, embeddings, retrieval, QA)Image / video model integration (optionally GANs, captioning, OCR)Build smart learning systems : time series forecasting, recommendations, knowledge graphsIntegrate token tracking, user usage monitoring, analytics🧑💻 Required Skills✅ Core
3–6+ years hands-on experience in AI / ML / LLM development and deploymentPython (advanced), OOPs, NumPy, Pandas, SQL (MySQL / PostgreSQL)Data preprocessing, EDA, model training / tuning / evaluationML algorithms (regression, classification, clustering)DL (ANN, CNN, RNN, LSTM, Transformer), GANsNLP (NER, summarization, sentiment, tokenization, embeddings)✅ Dev & Ops
FastAPI / Flask / Node.js (for backend API)Git, GitHub / Bitbucket, CI / CD pipelinesDocker, Kubernetes, AWS (EC2, Lambda, S3, Sagemaker, etc.)Redis, Supabase, Firebase, PostgreSQLGit-based testing, debugging, and logging practices✅ GenAI & LLM Stack
LangChain, LlamaIndex, OpenAI APIs, Bedrock modelsVector DBs (Qdrant, FAISS, pgvector)RAG architecture, memory layers, streaming AIAudio / Video AI tool integration (e.g., Whisper, AssemblyAI, Deepgram, WebRTC)Model fine-tuning, inference optimization (PEFT, LoRA, quantization)🌟 Bonus (Nice to Have)
Built, finetuned, trained or deployed LLM agents with real-world users or scaleExperience in K-12 EdTech, AI tutors, or learning platformsExposure to Lex, Connect, Step Functions, CloudWatch, IAM rolesFamiliarity with agent frameworks like LangGraph, AutoGen, CrewAIBasic frontend understanding (React, Next.js) to collaborate with full-stack teamsExperience with Agentic memory layer, prompt engineering , Agentic tools, RAG systems, MCP servers, Google's A2A protocol , vertex AI .🎓 Qualifications
B.E. / B.Tech / M.Tech in Computer Science, AI, Data Science, or related fieldsStrong coding and algorithmic reasoning skillsStrong written communication and technical documentation ability💼 Work Culture & Reporting
Team : Report to CTO and Founder, collaborate with AI agents, backend, and UI / UX teamsCulture : High ownership, agile delivery, startup intensity + deep tech creativityTools we use : GitHub, Linear, Slack, GCP, Supabase, Notion, Vercel, LangChain, AWS📩 How to Apply
Send your resume, GitHub, portfolio (if any), and links to AI / LLM projects you’ve built (not just notebooks) to :
📧 contact@yolearn.ai
🌐 www.yolearn.ai
