Senior Conversational AI Developer

6 days ago

Chennai, Tamil Nadu, India beBeeConversational Full time ₹ 20,00,000 - ₹ 25,00,000
About This Role

We are seeking a seasoned conversational AI developer to drive the development of our next-generation consumer AI product. This key role involves designing and implementing lightweight language models that generate safe, structured, and engaging interactions.

Responsibilities:
  • Narrative Engine Development: Design and implement pipelines for LLMs (Phi-2, TinyLLaMA, Mistral-small) to produce structured, interactive outputs.
  • Branching Narrative/Interaction Flows: Build deterministic continuation and constrained decoding algorithms for dynamic narrative paths.
  • Moderation and Safety Layers: Develop rule-based filters, toxicity detection using Detoxify, and integrate external moderation APIs (GPT/Claude).
  • Content Filtering and Vocabulary Control: Implement measures to enforce safe, compliant outputs and maintain content integrity.
  • Personalization and Progress Tracking: Develop heuristics-based personalization and progress tracking mechanisms for adaptive experiences.
  • Model Optimization: Optimize models for offline-first inference (quantization, ONNX, GGUF/ggml) with cloud fallback when needed.
  • Internal Tools Development: Create internal tools for prompt/template management, content testing, and moderation review.
  • Integration with Speech AI: Collaborate with the Speech AI Engineer to seamlessly integrate text generation and voice pipeline.
  • Observability Metrics: Define metrics for latency, generation success, and moderation outcomes.
Requirements:
  • 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.

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