Outcome Engineer - Early in Career Professional

Onebrief
United States | RemotePosted 7 April 2026

Job Description

Outcome Engineer - Early in Career Professional ABOUT ONEBRIEF Onebrief is collaboration and AI-powered workflow software designed specifically for military staffs. By transforming this work, Onebrief makes the staff as a whole superhuman - meaning faster, smarter, and more efficient. We take ownership, seek excellence, and play to win with the seriousness and camaraderie of an Olympic team. Onebrief operates as an all-remote company, though many of our employees work alongside our customers at military commands around the world. Founded in 2019 by a group of experienced planners, today, Onebrief’s team spans veterans from all forces and global organizations, and technologists from leading-edge software companies. We’ve raised $320m+ from top-tier investors, including Battery Ventures, General Catalyst, Sapphire Ventures, Insight Partners, and Human Capital, and today, Onebrief is valued at $2.15B. With this continued growth, Onebrief is able to make an impact where it matters most. We are also defining the future of software development. We believe the era of "human bandwidth" as the primary constraint on software delivery is ending. We are building a dedicated team to transition our organization from Software Engineering to Outcome Engineering. ABOUT THE ROLE You’re an AI-native engineer who is living the future of software development now. You start your day checking Hugging Face, and have 3 side hustles running based on agentic apps you’ve shipped. You’re ready to bring your curiosity and willingness to quickly embrace new technologies to a team that is collectively creating Onebrief’s AI Engineering Platform. As an Outcome Engineer, you’ll join a team whose whole is greater than the sum of its parts - a true melting pot of backgrounds and experiences focused on transforming the possibilities created by AI into realities. This is neither just prompt building nor model development. You will be part of a team building the factory that builds the software. You will help move us from a world of managed backlogs to a world of infinite execution, creating the foundation of what product development becomes in an agentic world. We are looking for pioneers. WHAT YOU'LL DO - Architect Multi-Agent Systems: Design the orchestration layers that enable multiple specialized agents to collaborate, debate, and execute complex tasks reliably. You will move us from simple prompts to robust, stateful agentic workflows. - Implement Automated Governance: Create the "guardrails" and policy engines that allow autonomous systems to operate safely at speed. You will build the infrastructure that replaces manual review with programmatic constraints. - Engineer Context and Memory: Build the semantic infrastructure (knowledge graphs, vector stores) that provides agents with deep, structural understanding of our codebase and business intent. You will solve the "blank slate" problem for autonomous workers. - Build Rigorous Evaluation Frameworks: Develop the testing harness that defines success. You will move us beyond "vibes" to deterministic validation of agentic outputs using formal specifications and automated metrics. - Design Self-Healing Loops: Connect observability data directly to agent actions, enabling systems that not only detect failures but autonomously analyze and remediate them. - Prototype and Deploy: We prove success by shipping. You will rapidly prototype new agentic tools and deploy them to production for both our internal teams and customers. This is a creation role; we learn by building. - Experiment and Learn: This is a new field. You will be experimenting with new models, new orchestration techniques, and new ways of validating agent behavior every day. WHAT WE LOOK FOR We are casting a wide net. While strong software engineering skills are valuable, we believe the best Outcome Engineers might come from diverse backgrounds, that interdisciplinary backgrounds and an embrace of ego-free collaboration is key to in ... (truncated, view full listing at source)
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