Visionary AI Architect

3 days ago

Kolkata, West Bengal, India beBeeArtificialIntelligence Full time ₹ 20,00,000 - ₹ 25,00,000
Job Title:

Artificial Intelligence Engineer

Job Description:

We're seeking a talented AI engineer to join our team and help shape the future of artificial intelligence. As an AI engineer, you'll be responsible for designing and implementing intelligent systems that can reason, plan, and interact autonomously in real-world applications.

You will collaborate with a highly collaborative team to develop systems leveraging Large Language Models (LLMs), contextual memory, and tool integration – delivering AI-native applications rather than traditional ML pipelines.

  • AI System Development: Design and implement agent-oriented systems supporting task decomposition, memory handling, and contextual planning.
  • Framework Engineering: Develop and extend our in-house AI Agent Framework with reusable components like tools, memory modules, and orchestration logic.
  • Contextual Intelligence: Build and integrate vector search, semantic retrieval, and memory systems to enable long-term, goal-driven agent behavior.
  • Natural Language Interfaces: Connect LLMs (e.g., OpenAI, Anthropic) and NLU/NLP layers to enable natural task inputs and autonomous reasoning capabilities.
  • API Engineering: Develop RESTful APIs using FastAPI, Flask, or Django to expose agent capabilities and integrate with other products.
  • System Architecture: Design scalable, event-driven microservice architectures tailored for AI-native workloads and agent frameworks.
  • Ethical AI: Prioritize responsible AI design with user safety, transparency, and privacy at the core.

Required Skills & Qualifications:

  • Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.
  • Python Proficiency: Strong software engineering skills in Python (3.x) with deep understanding of async programming, architecture design, and typing.
  • AI/LLM Experience: Practical experience of 3 YEARS using LLMs for reasoning, prompt engineering, chaining, or building agent-like applications.

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