Innovative System Architect

2 days ago

Anand, Gujarat, India beBeeArtificial Full time US$ 1,50,000 - US$ 1,70,000
Intelligent Systems Designer

We are seeking a highly skilled and motivated professional to design, build, and scale intelligent systems.

  • Key Responsibilities
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  • Design, prototype, and deploy AI LLM-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.
  • Stay current with cutting-edge AI research, frameworks, and methodologies and assess their potential for production use.
  • Collaborate with cross-functional teams including product, design, and backend to integrate intelligent features seamlessly.
  • Document technical decisions, model behavior, system limitations, and assumptions in a clear and accessible manner.

Required Skills Experience

  1. 3-4 years of hands-on experience in AI ML, data engineering, or full-stack development, with a strong foundation in intelligent system design.
  2. Deep understanding of Large Language Models LLMs including concepts like embeddings, context windows, transformers, token limits, and memory strategies.
  3. Proven experience implementing RAG pipelines and working with vector databases and Knowledge Graphs.
  4. Familiarity with GenAI frameworks and orchestration tools such as LangChain, LlamaIndex, or similar.
  5. Proficiency in Python and experience developing backend logic and integrating with APIs.
  6. Awareness of ethical and security concerns in AI including safety, fairness, and responsible deployment.
  7. Ability to assess and articulate trade-offs in system design e.g., cloud vs. edge deployment, fine-tuning vs. prompt engineering, open vs. closed models.

Preferred Qualifications Nice to Have

  • 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.
  • Familiarity with AI observability, logging, and monitoring best practices.
  • Contributions to the AI community, such as open-source projects, research papers, blog posts, or talks.

What We Offer

  • Competitive compensation and performance-based bonuses.
  • Opportunities for learning, research, and career growth in cutting-edge AI technologies.
  • A collaborative, transparent, and inclusive work environment.

Skills

  1. Generative AI
  2. RAG pipelines
  3. Python
  4. API integration
  5. AI LLM

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