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Senior AI Engineer – GenAI Systems & AI Agent Architecture

Senior AI Engineer – GenAI Systems & AI Agent Architecture

YoLearn.AIerode, tamil nadu, in
1 day ago
Job description

📌 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 engineering
  • Build 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 workflows
  • Integrate 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 graphs
  • Integrate token tracking, user usage monitoring, analytics
  • 🧑‍💻 Required Skills✅ Core

  • 3–6+ years hands-on experience in AI / ML / LLM development and deployment
  • Python (advanced), OOPs, NumPy, Pandas, SQL (MySQL / PostgreSQL)
  • Data preprocessing, EDA, model training / tuning / evaluation
  • ML algorithms (regression, classification, clustering)
  • DL (ANN, CNN, RNN, LSTM, Transformer), GANs
  • NLP (NER, summarization, sentiment, tokenization, embeddings)
  • ✅ Dev & Ops

  • FastAPI / Flask / Node.js (for backend API)
  • Git, GitHub / Bitbucket, CI / CD pipelines
  • Docker, Kubernetes, AWS (EC2, Lambda, S3, Sagemaker, etc.)
  • Redis, Supabase, Firebase, PostgreSQL
  • Git-based testing, debugging, and logging practices
  • ✅ GenAI & LLM Stack

  • LangChain, LlamaIndex, OpenAI APIs, Bedrock models
  • Vector DBs (Qdrant, FAISS, pgvector)
  • RAG architecture, memory layers, streaming AI
  • Audio / 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 scale
  • Experience in K-12 EdTech, AI tutors, or learning platforms
  • Exposure to Lex, Connect, Step Functions, CloudWatch, IAM roles
  • Familiarity with agent frameworks like LangGraph, AutoGen, CrewAI
  • Basic frontend understanding (React, Next.js) to collaborate with full-stack teams
  • Experience 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 fields
  • Strong coding and algorithmic reasoning skills
  • Strong written communication and technical documentation ability
  • 💼 Work Culture & Reporting

  • Team : Report to CTO and Founder, collaborate with AI agents, backend, and UI / UX teams
  • Culture : High ownership, agile delivery, startup intensity + deep tech creativity
  • Tools 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

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