Research Engineer

Research Engineer Full-time/Company: Gauntlet Gauntlet builds the financial systems of the future, operating across the onchain finance stack and serving institutional clients with best-in-class vault products. They support over $1.7B in client TVL across fintechs, protocols, exchanges and traditional asset managers. Applicants must be able to work within the contiguous United States and Canada. Responsibilities: - Build evaluation frameworks for AI agents, including datasets, sandbox environments and metrics for real-world tasks. - Design experiments to compare models, agent harnesses, tools and execution environments to identify regressions and trade-offs. - Turn qualitative feedback about agent behaviour into concrete research questions, experiments and measurable outcomes. - Investigate agent failures to determine root causes (model, harness, tooling, prompting) and improve performance. - Build and improve agent harnesses, internal tools and integrations, including contributing to Aria and other agents. - Develop shared knowledge and reusable skills across agents so systems can learn and improve over time. - Collaborate with Infrastructure and Security to ensure agents operate reliably and safely in production. Requirements: - Hands-on experience building, evaluating or improving LLM models or agents (professional, research, open-source or personal projects). - Strong Python skills and solid software engineering fundamentals; able to write production-quality, tested code. - Experience with applied research, machine learning or data science, including experiment design and dataset work. - Understanding of how LLM agents work beyond prompting: tool use, harnesses, context management and failure modes. - Ability to decompose open-ended problems into testable questions and work independently toward solutions. - Experience building tools or systems for other teams, with attention to evaluating effectiveness beyond benchmarks. - Comfortable collaborating across research and engineering and adapting to changing priorities. Nice to have: - Experience building LLM evaluation pipelines, benchmarks, RL environments or model testing infrastructure. - Contributions to open-source agent frameworks, harnesses, evaluation datasets or benchmarks. - Experience with agent frameworks such as Hermes, OpenClaw or similar tools. - Experience in applied ML research, model training, fine-tuning or reinforcement learning. - Advanced degree or postgraduate research experience in CS, mathematics, statistics, ML or related field. - Experience in financial markets, quantitative research, DeFi or risk modelling. - Familiarity with AI security considerations, including access controls, prompt injection and data protection. Stack: Python, LLMs, agent frameworks (Hermes, OpenClaw), reinforcement learning, fine-tuning Benefits: - Remote first — work from anywhere in the United States - Regular in-person company retreats and cross-country "office visit" perk - 100% paid medical, dental, and vision premiums for employees - $1,000 WFH stipend - Monthly reimbursement for home internet, phone, and cellular data - Unlimited vacation - 100% paid parental leave of 12 weeks - Fertility benefits - Opportunity for incentive compensation - National pay range: $175,000 - $195,000 base plus additional On Target Earnings potential and equity 📩 Apply