Voice AI Engineer for a Seed-Stage EdTech Startup (AI-Powered Learning for Young Children) – B2C

Overview

Key Responsibilities

• Design, develop, and optimize conversational AI systems, including chatbots, voicebots,
and virtual assistants.
• Build, fine-tune, and evaluate NLP/LLM-based models for intent classification, entity
extraction, summarization, and dialogue management.
• Architect and implement end-to-end conversational flows, ensuring high accuracy,
contextual understanding, and natural interactions.
• Collaborate with product teams to define user journeys and create high-quality
conversation designs.
• Implement evaluation frameworks to monitor model performance, accuracy, latency, and
user satisfaction.
• Work with engineering teams to deploy models into production environments at scale.
• Conduct A/B tests, collect feedback, and continuously improve model behavior.
• Stay updated on the latest advancements in LLMs, generative AI, prompt engineering, and
dialogue systems.

*Skills & Qualifications *

• 4–9 years of hands-on experience building conversational AI products (chatbots,
assistants, NLU pipelines, LLM apps, voice interfaces).
• Strong knowledge of NLP, NLU, NLG, machine learning, and deep learning techniques.
• Experience with frameworks such as Rasa, Dialogflow, IBM Watson, Botpress, LangChain,
LlamaIndex, or custom-built dialogue systems.
• Proficiency in Python and ML libraries (TensorFlow, PyTorch, Hugging Face, spaCy).
• Experience with LLMs (OpenAI, GPT, Llama, Claude, Gemini & fine-tuning APIs).
• Understanding of prompt engineering, retrieval augmentation (RAG), and model
evaluation methods.
• Experience integrating conversational systems with APIs, databases, CRMs, or enterprise
systems.
• Strong problem-solving skills with the ability to work in fast-paced environments.
• Excellent communication and collaboration abilities.

*Preferred Qualifications *

• Experience shipping conversational AI products at scale (consumer or enterprise).
• Knowledge of speech technologies (ASR, TTS).
• Understanding of cloud platforms (AWS, GCP, Azure).
• Experience with analytics for conversational systems (user journeys, funnel analysis).
• Prior work in startup or product-driven environments.