About usHear is an innovative early-stage startup dedicated to shaping the future of conversational intelligence. We are passionate about AI, technology, and addressing real-world challenges. We uphold high safety standards for our products and foster a collaborative environment with exceptional people.About the roleWe’re looking for an AI Engineer to design, build, and deploy next-generation AI systems powering Hear’s conversational analytics and agentic intelligence platform.This role is ideal for someone who loves pushing LLM capabilities forward, enjoys experimenting with autonomous AI frameworks, and stays ahead of the curve on emerging AI technologies. You’ll work with tools like LangChain, LangGraph, Claude, Cursor, and Pydantic AI - and optimize deployments using vLLM and GCP.Responsibilities- Design, develop, and optimize AI models for conversational intelligence, analytics, and autonomous workflows.- Build LLM-based systems leveraging LangChain, LangGraph, and similar orchestration frameworks.- Integrate Claude and other LLM APIs into production-ready applications.- Use Cursor and AI-assisted coding workflows to accelerate model prototyping and deployment.- Fine-tune large language models (LLMs) for task-specific use cases and evaluate performance improvements.- Deploy and scale inference using vLLM or equivalent high-performance serving frameworks.- Implement and manage monitoring, logging, and performance tracking with DataDog.- Work closely with cross-functional teams to integrate AI pipelines into customer-facing products deployed on GCP.- Stay up to date with the latest AI research, frameworks, and tools to continuously improve our platform’s capabilities.Qualifications- At least 4 years of hands-on experience with machine learning/AI frameworks is required- Practical experience with LLM frameworks such as LangChain, LangGraph, or equivalent.- Familiarity with AI-assisted coding tools (e.g., Cursor, Copilot).- Bachelor’s or Master’s degree in Computer Science or a related field with a focus on AI/ML.- Familiarity with GCP/AWS, efficient inference serving for large language models (advantage), and deployment/monitoring of AI systems in production, including the use of DataDog.- Excellent problem-solving abilities and a passion for innovation.