As a Senior AI Engineer, you'll be architecting the intelligence that powers Figr's design platform. You'll build sophisticated multi-agent systems that understand design context, retrieve relevant information across vast design spaces, and maintain coherent conversations with users throughout complex design workflows. The Core Responsibilities For The Job Include The Following AI Infrastructure and Architecture: Lead AI infrastructure in production environments. Design and implement multi-agent systems with deep retrieval capabilities. Build robust context management systems that maintain design intent across sessions. Optimize agent coordination, communication patterns, and decision-making workflows. Product And Research Integration Translate cutting-edge AI research into working features that designers actually use. Implement advanced retrieval-augmented generation (RAG) systems for design knowledge. Build context-aware agents that understand design patterns, user preferences, and project history. Work closely with founders and the early team to shape product direction. Technical Leadership Drive core technical and product decisions around AI capabilities. Establish best practices for agent evaluation, monitoring, and continuous improvement. Scale AI systems to handle complex, multi-step design workflows. Own the full stack from model fine-tuning to production deployment. Requirements Production AI Experience: Built AI agents in production with real users (web-socket, async, gRPC). Multi-Agent Systems: Experience implementing and evaluating complex agent architectures. Retrieval and Context: Deep experience with RAG systems, vector databases, and context management. Strong Engineering: Solid software engineering fundamentals with a focus on scalable, maintainable systems. Communication: Clear communication with engineers, designers, and non-technical stakeholders. Nice To Have Experience with design tools, creative workflows, or visual AI. Like to do product thinking and how to shape the product. Previous startup experience in fast-paced, high-ownership environments. Tech Stack You'll Work With AI/ML: OpenAI, Anthropic, or similar LLM APIs. Retrieval: Vector databases (Pinecone, Weaviate, Chroma). Backend: Python, HTTP/2 connections, async processing. Infrastructure: Cloud platforms (AWS/GCP), Docker, and monitoring tools. Tools: Cursor for development, internal tooling as needed. This job was posted by Chirag Singla from Figr.