Unusual

Unusual Ventures is seeking an AI Engineer to join their team. This role involves building AI-powered agents and pipelines to enhance talent intelligence, sourcing, and research for their portfolio companies. You will also develop tools for diligence support, firm knowledge management, operations automation, and portfolio support, directly impacting the firm's usefulness to the founders they back. The position emphasizes building practical solutions that address real user problems and iterating quickly.

We are seeking a Staff/Senior Software Engineer to join our Agent Engineering team, focusing on the Helios project. This role involves building and strengthening the foundations of our agent runtime, enabling the creation of new agent-driven products. You will develop systems that allow agents to manage long-running work from assignment to completion, ensuring agent activity is visible, steerable, and connected to relevant projects, people, evidence, deadlines, and deliverables. Additionally, you will construct the framework for agents to safely interact with internal systems and external services, and connect agents to our retrieval and knowledge systems to ground their reasoning, memory, citations, and generated artifacts in authoritative evidence. A key part of this role is improving the evaluation and release discipline for agent behavior, traces, and simulations to enhance quality while controlling latency, cost, and risk.

We are seeking a Principal AI Engineer to provide hands-on technical leadership for complex, production-grade AI systems. This is a deeply technical builder role focused on defining technical direction through coding, system design, and enabling teams to move faster and scale effectively. You will architect and build end-to-end AI systems, including LLM orchestration, retrieval layers, agentic workflows, and structured reasoning systems, while leading the design of multi-agent and tool-calling systems for reliable production operation. The role involves establishing architecture patterns for scalable, cost-aware, and observable AI applications, driving technical decisions across data modeling, AI pipelines, infrastructure, and APIs, and defining best practices for evaluation, monitoring, and governance.