Safe AI Architect

1 week ago


Dindigul, Tamil Nadu, India beBeeData Full time ₹ 15,00,000 - ₹ 25,00,000
Key Role in AI Safety

We are seeking a highly skilled Data Scientist to play a pivotal role in designing and building effective Large Language Model (LLM) guardrails. Your primary objective will be to protect against unwanted behavior in LLMs, ensuring safety and fairness in AI-driven applications.

Responsibilities
  • Guardrail Development: Develop and implement effective strategies to prevent prompt injection, toxicity, bias detection, and hallucination/jailbreak identification.
  • Evaluation Frameworks: Create and maintain evaluation frameworks to monitor LLM performance, identifying areas for improvement and ensuring compliance with regulatory standards.
  • Pipeline Development: Design and implement automated pipelines using Python and SQL to process, tag, and evaluate LLM outputs, improving efficiency and accuracy.
  • Vector Database Integration: Leverage vector databases and embeddings to detect unsafe content or model drift, enhancing overall system reliability.
  • Dashboard Creation: Create interactive dashboards and visualizations using Streamlit, Dash, or lightweight React/JS for proof-of-concepts and internal tools, facilitating data-driven decision-making.
  • Collaboration and Integration: Work closely with ML engineers and product teams to integrate LLM safety components into production APIs or applications, ensuring seamless integration.

To excel in this role, you will require 1-3 years of experience in data science, applied machine learning, or LLM-based applications. Strong programming skills in Python and experience writing SQL for data exploration or feature engineering are essential. A solid understanding of natural language processing, deep learning, and LLM architectures is also necessary.

  • Hands-on experience with Hugging Face, LangChain, LLM APIs (OpenAI, Anthropic), and vector stores (FAISS, Pinecone, Chroma).
  • Familiarity with front-end basics (Streamlit, Dash, or simple HTML/CSS/JS) is a plus, not mandatory.
  • Experience with model evaluation, red-teaming, or safety interventions in NLP/LLM systems.
  • (Preferred) Familiarity with deploying ML pipelines in production (Docker, FastAPI) and ability to thrive in a fast-paced startup environment.

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