Research Engineer

Gauntlet; United States; Remote; USD 175,000 - 195,000; Full time

Benefits offered by this job

Remote work from anywhere in US

Company retreats

Medical, dental, vision insurance

WFH stipend

Internet/Home cell reimbursement

Unlimited vacation

Parental leave (12 weeks)

Equity opportunity

Job summary

Gauntlet is hiring an AI Research Engineer to enhance how we build, evaluate, and deploy AI agents across the business. You will design evaluation frameworks, run real-world experiments, and translate findings into production-ready improvements.

The role blends applied research with engineering and offers opportunities to influence Aria and other agents. We seek hands-on researchers who can work independently, design rigorous experiments, and collaborate across teams to scale robust agent

Qualifications

• Experience building, evaluating or improving LLM models or agents.
• Strong Python and software engineering fundamentals.
• Ability to write production-quality code and test software.
• Applied ML or data science experience with experiments and datasets.
• Understanding of LLM agents, tool use, context management and failure modes.

Responsibilities

• Build evaluation frameworks for AI agents with datasets, sandbox environments and metrics.
• Design experiments to compare models, agents and tooling; identify regressions and trade-offs.
• Translate qualitative feedback into research questions and measurable outcomes.
• Investigate agent failures and improve performance across models, harnesses and prompting.
• Contribute to Aria and other internal agents; ship integrations and tooling.
• Develop shared knowledge and reusable agent skills for the team.
• Collaborate with Infrastructure and Security to ensure safe production operation.

Skills

Python

Experiment design

Research

Agent evaluation

Independent work

Collaboration

AI safety

Education

Advanced degree in CS/Math/ML

Tools

Hermes

OpenClaw

Job description

Research Engineer

New York City / San Francisco / Los Angeles / Remote

Engineering / Full Time / Remote

The role Gauntlet is looking for an AI Research Engineer to help improve how we build, evaluate and use AI agents across the business. We already have agents running in production, including Aria, our in-house generalist agent. They are used across research, engineering and business workflows, and we’ve learned a lot from seeing how they perform in practice. Some tasks work extremely well; others produce inconsistent results, and changes to models or tooling can introduce unexpected problems. Today, much of that feedback is still subjective. We want to build a more systematic way of understanding what works, what doesn’t and why. A major part of this role will be building the evaluation frameworks that allow us to measure agent performance on real tasks. You’ll work with our engineers, quantitative researchers and other teams to understand where agents struggle, turn those observations into measurable experiments, and use the results to improve the systems we’re building. You’ll also contribute directly to our existing agents and internal tooling. Initially, the work will be more engineering-focused as you get familiar with our systems, shipping improvements and integrations that teams can use. Over time, you’ll take on more open-ended research, helping us develop better approaches to evaluation, agent behavior and infrastructure. We’re also thinking beyond individual agents. One of our longer-term goals is to build a shared system of knowledge and reusable skills that our agents can draw from and improve over time. You’ll play an important role in developing that infrastructure and how we evaluate its effectiveness. This is an applied research role with a meaningful engineering component. We’re looking for someone who enjoys investigating difficult problems, can design good experiments and is comfortable building and shipping the solutions that come out of them.

About Gauntlet

Gauntlet builds the financial systems of the future. While much of onchain finance is focused on point solutions, we operate across the entire stack to offer best-in-class vault products. Today we serve over $1.7B in client TVL across some of the largest fintechs/neobanks, protocols, exchanges, and capital allocators in crypto - and, increasingly, traditional asset management. Our team brings together traditional finance and crypto-native expertise to deliver durable, sophisticated products for institutional clients moving onchain.

Why this role is different

This is an opportunity to work at the intersection of AI, quantitative research and DeFi, tackling problems where advances in AI can have a direct impact on financial markets and onchain strategies. You’ll go beyond building individual agents, helping define how they’re evaluated, how they learn from real-world tasks and how their capabilities scale across the business. With few established benchmarks in this space, you’ll have the freedom to explore new approaches and take your ideas from research through to production, working directly with the teams putting them to use.

What you ll do

• Build evaluation frameworks for AI agents, including datasets, sandbox environments and metrics that measure performance on real-world tasks.
• Design experiments to compare models, agent harnesses, tools and execution environments, identifying regressions and understanding the trade-offs between performance, reliability and cost.
• Work with teams across Gauntlet to turn qualitative feedback about agent behavior into concrete research questions, experiments and measurable outcomes.
• Investigate agent failures, understand whether problems come from the model, harness, tooling or prompting, and develop ways to improve performance.
• Build and improve agent harnesses, internal tools and integrations, including contributing to Aria and other agents used across the business.
• Help develop shared knowledge and reusable skills across agents, creating systems that can learn from previous work and improve over time.
• Work alongside Infrastructure and Security to ensure agents can operate reliably and safely within our production environment.

What we re looking for

• Hands-on experience building, evaluating or improving LLM models or agents, whether through professional work, applied research, open-source contributions or substantial personal projects.
• Strong Python skills and good software engineering fundamentals.
• You’re comfortable writing production-quality code and understand the importance of testing, maintainability and reliability.
• Experience with applied research, machine learning or data science, including designing experiments, working with datasets and drawing conclusions from results.
• A good understanding of how LLM agents work beyond prompting, including tool use, harnesses, context management and common failure modes.
• The ability to take an open-ended problem, break it down into testable questions and work independently towards a solution.
• Experience building tools or systems that other people use, with an understanding of how to evaluate their effectiveness beyond technical benchmarks.
• Comfort working across research and engineering, collaborating with different teams and adapting as priorities change.
• Genuine interest in AI agents and how they can be made more capable, reliable and useful.

Nice to have

• Experience building LLM evaluation pipelines, benchmarks, reinforcement learning 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.
• An advanced degree or postgraduate research experience in computer science, mathematics, statistics, machine learning or a 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.
• You don’t need prior experience in crypto or DeFi. Strong research and engineering fundamentals matter more, and you’ll work closely with people across Gauntlet who understand the financial systems and strategies our agents support.
• We expect strong candidates to have experience working in a professional engineering or research environment, but we’re more interested in what you’ve built and how you approach problems than a specific number of years on your CV.

Benefits & Perks

• 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

Please note

At this time our hiring is reserved for potential employees who are able to work within the contiguous United States and Canada. Should you need alternative accommodations, please note that in your application.

Salary

The national pay range for this role is $175,000 - $195,000 base plus additional On Target Earnings potential by level and equity in the company. Our salary ranges are based on paying competitively for a company of our size and industry, and are one part of many compensation, benefits and other reward opportunities we provide. Individual pay rate decisions are based on a number of factors, including qualifications for the role, experience level, skill set, and balancing internal equity relative to peers at the company.

#LI-Remote

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.