Role and Responsibilities Design and implement agentic workflows powered by LLMs for real-world task execution. Build customization layers tailored to organization-specific logic. Develop voice-based and message-based learning agents that drive engagement. Architect AI pipelines with evaluation, feedback loops, and continuous monitoring. Architect scalable, reliable infrastructure and integrate into complex environments. Experience with Rails is a bonus, but not required. Manage multi-agent orchestration and core AI system infrastructure. Required Qualifications: Machine Learning Expertise 5+ years experience in ML (PyTorch, Tensor Flow). 2+ years experience with Large Language Models (Hugging Face, OpenAI, Anthropic). AI System Development Experience in building and deploying production AI systems, including RAG and vector search. Knowledge of prompt engineering, AI safety, and content filtering best practices. Technical Proficiency Familiarity with Rails is a plus, but not required, Strong candidates could be onboarded as needed. Experience working with REST APIs, PostgreSQL, ActiveRecord, and RSpec is helpful. Understanding of LangChain, LlamaIndex, or similar frameworks, or ability to ramp up quickly.