AI Engineer

About the Role We're looking for an AI Engineer to design, build, and scale the systems that power our AI-driven product. You'll work at the intersection of large language models, multi-agent systems, and production software, turning cutting-edge AI capabilities into reliable, user-facing experiences. What You'll Do Design and implement LLM-powered pipelines, including prompt engineering, context management, and response synthesis Build and optimize multi-agent orchestration systems where AI components interact, reason, and produce coherent outputs Develop and maintain integrations with foundation model APIs (Anthropic, OpenAI, and others), managing latency, cost, and reliability at scale Implement retrieval-augmented generation (RAG) and memory systems for persistent, context-aware behavior Partner with the Evaluation/QA Engineer to build frameworks that measure output quality, coherence, and factual grounding Collaborate with product and design to translate workflows into robust technical experiences Ship production features across the stack, from the model layer to the application Monitor, debug, and improve system performance, token efficiency, and guardrails 3+ years of software engineering experience, with hands-on work building LLM-powered applications Strong proficiency in Python and/or TypeScript/JavaScript Experience with LLM APIs, prompt engineering, and agentic frameworks (e.g., LangChain, LlamaIndex, or custom orchestration) Familiarity with vector databases and RAG architectures (Pinecone, Weaviate, pgvector, etc.) Understanding of multi-agent systems, tool use, and function calling Experience designing evaluation and testing strategies for non-deterministic AI outputs Solid grasp of API design, async processing, and scalable backend architecture Comfort working in a fast-moving, ambiguous, early-stage environment Experience with real-time streaming (WebSockets, SSE) for conversational interfaces Background in fine-tuning, model distillation, or inference optimization Familiarity with cloud infrastructure (AWS/GCP/Azure) and CI/CD Contributions to open-source AI projects