AI Engineering Lead

6 days ago

Rajahmundry, Andhra Pradesh, India beBeeArtificial Full time ₹ 20,00,000 - ₹ 25,00,000

About our Consumer AI Product

We are looking for an experienced AI Engineer to design and implement the narrative engine, content generation, safety/moderation systems, and personalization logic.

The role involves building lightweight, optimized language models that generate safe, structured, and engaging interactions for a next-generation consumer AI product.

  • Design and implement lightweight LLM pipelines (Phi-2, TinyLLaMA, Mistral-small) for structured, interactive outputs.
  • Build branching narrative/interaction flows with deterministic continuation and constrained decoding.
  • Develop moderation and safety layers: rule-based filters, toxicity detection, and fallback to external moderation APIs.
  • Apply content filtering and vocabulary controls to enforce safe, compliant outputs.
  • Implement heuristics-based personalization and progress tracking for adaptive experiences.
  • Optimize models for offline-first inference (quantization, ONNX, GGUF/ggml) with cloud fallback when needed.
  • Build internal tools for prompt/template management, content testing, and moderation review.
  • Work closely with the Speech AI Engineer to integrate text generation voice pipeline seamlessly.
  • Define observability metrics (latency, generation success, moderation outcomes).

Qualifications:

  • 5+ years of professional experience in applied AI/NLP, with at least 3 years focused on LLMs or conversational AI.
  • Strong background in language models: fine-tuning, LoRA, adapter methods, prompt engineering.
  • Proficiency in PyTorch; experience serving models with FastAPI/Docker.
  • Experience with edge optimization: quantization, batching, caching.
  • Knowledge of structured AI outputs (JSON schemas, branching graphs).
  • Hands-on with content moderation systems and multi-layer safety approaches.
  • Understanding of privacy and compliance requirements for consumer AI apps.

Nice to Have:

  • Experience with dialogue systems or conversational assistants.
  • Exposure to personalization/recommendation systems.
  • Familiarity with educational/narrative applications.
  • Graduated from top-tier colleges.

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