AIML Engineer

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Role Overview:

AI Engineer

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.