Intelligent System Designer

3 days ago

Bikaner, Rajasthan, India beBeeDataEngineer Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

Seeking a Data Engineer with expertise in intelligent system design.

Job Description

We are looking for a talented Data Engineer to join our team. As a key member of our organization, you will be responsible for designing and building intelligent systems that drive business outcomes. Your expertise in large language models, vector databases, and knowledge graphs will enable us to create innovative solutions that meet the needs of our customers.

  • Design and develop AI/ML enabled applications with a focus on modularity, scalability, and maintainability.
  • Develop and fine-tune RAG pipelines tailored for enterprise or product-based use cases, optimizing for retrieval relevance and accuracy.
  • Work with unstructured data — documents, transcripts, APIs — and transform them into structured knowledge systems using embeddings, vector stores, and knowledge graphs.
  • Evaluate and select appropriate GenAI tools, frameworks, and models, balancing performance, latency, cost, and data security.
  • Monitor application behavior and refine prompts, retrieval logic, and context engineering to enhance response quality.
  • Identify and communicate system edge cases and risks — including hallucination, bias, prompt injection, and model over-reliance.
Required Skills & Experience:
  • 3–4 years of hands-on experience in AI/ML, data engineering, or full-stack development, with a strong foundation in intelligent system design.
  • Deep understanding of Large Language Models (LLMs) — including concepts like embeddings, context windows, transformers, token limits, and memory strategies.
  • Proven experience implementing RAG pipelines and working with vector databases and Knowledge Graphs.
  • Familiarity with GenAI frameworks and orchestration tools such as LangChain, LlamaIndex, or similar.
  • Proficiency in Python and experience developing backend logic and integrating with APIs.
  • Awareness of ethical and security concerns in AI — including safety, fairness, and responsible deployment.
Preferred Qualifications:
  • Exposure to open-source LLMs and toolkits (e.g., Llama, Mistral, Claude, etc.).
  • Experience with evaluation metrics, benchmarking, or implementing human-in-the-loop feedback systems.

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