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LD

Artificial Intelligence Engineer

LLM Decode
Posted 2 hours ago
🇮🇳India🏠Remote📁Engineering & Development
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We're looking for a passionate AI Engineer to design, develop, and deploy production-grade AI applications powered by Large Language Models. You'll collaborate with a distributed team to build scalable AI solutions that solve real-world business challenges.


Key Responsibilities

  • Design and develop AI-powered applications using OpenAI, Anthropic, Gemini, or open-source LLMs.
  • Build Retrieval-Augmented Generation (RAG) pipelines using vector databases and embedding models.
  • Develop AI agents and multi-agent workflows using frameworks such as LangGraph, LangChain, CrewAI, or LlamaIndex.
  • Integrate AI capabilities into web applications and backend services.
  • Engineer prompts, evaluate model performance, and optimize for quality, latency, and cost.
  • Deploy scalable AI services using Docker, Kubernetes, and cloud platforms (AWS, Azure, or GCP).
  • Implement monitoring, evaluation, and observability for production AI systems.
  • Collaborate with cross-functional teams in a remote environment to deliver AI features from concept to production.
  • Stay up to date with the latest advancements in Generative AI and apply them to product development.


Required Skills

  • Strong proficiency in Python.
  • Experience building applications with LLM APIs.
  • Hands-on experience with RAG, embeddings, and vector databases (Pinecone, Weaviate, ChromaDB, FAISS, or Milvus).
  • Experience with LangChain, LangGraph, LlamaIndex, or similar AI frameworks.
  • Familiarity with FastAPI or Flask for backend development.
  • Understanding of prompt engineering, function calling, and agentic workflows.
  • Experience with Git, Docker, CI/CD, and cloud deployment.
  • Strong analytical and problem-solving skills.

Preferred Qualifications

  • Experience with fine-tuning or deploying open-source LLMs.
  • Knowledge of MCP (Model Context Protocol), AI workflow orchestration, or LLMOps.
  • Familiarity with evaluation frameworks, guardrails, and observability tools.
  • Experience building production-grade AI products.


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