AIML Engineer

2 days ago

Pune Maharashtra India, Maharashtra Atyeti Inc Full time

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Role Overview:

We are seeking a highly skilled AI Engineer to design and implement intelligent systems using agentic AI capable of autonomous decision-making and task execution. This role involves integrating advanced machine learning models with reasoning, planning, and interaction capabilities to build scalable, intelligent applications. The ideal candidate will have a strong foundation in LLMs, prompt engineering, and web development, with hands-on experience deploying AI-powered web applications.


Key Responsibilities:

  • Design and develop agentic AI systems with autonomous task execution capabilities.
  • Integrate Large Language Models (LLMs) with reasoning, planning, and interaction frameworks.
  • Implement Retrieval-Augmented Generation (RAG) architectures using vector databases.
  • Engineer effective prompts and workflows for LLM-based agents.
  • Utilize agentic libraries (e.g., LangChain, AutoGPT, CrewAI, etc.) to build modular and scalable AI agents.
  • Develop and deploy web applications that interface with AI systems.
  • Collaborate with cross-functional teams to define system requirements and deliver robust solutions.
  • Optimize performance, scalability, and reliability of AI-powered applications.


Must-Have Skills:

  • Programming: Proficiency in Python and relevant AI/ML libraries.
  • LLMs: Experience working with models like GPT, Claude, Mistral, or open-source equivalents.
  • Prompt Engineering: Ability to design and refine prompts for complex tasks.
  • Vector Databases: Hands-on experience with FAISS, Pinecone, Weaviate, or Chroma.
  • RAG Architecture: Deep understanding of retrieval-based generation pipelines.
  • Agentic Libraries: Familiarity with frameworks like LangChain, AutoGPT, CrewAI, or similar.
  • Web Development: Prior experience in frontend/backend development and web app deployment (e.g., using Flask, FastAPI, React, Docker).
  • Deployment: Experience deploying applications on cloud platforms (AWS, Azure, GCP) or containerized environments.

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