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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.