Senior Research Engineer, Applied AI

Description

The Cato Institute seeks qualified candidates for the Senior Research Engineer, Applied AI position. AI tools are proliferating rapidly. Making them genuinely useful for policy research requires someone who bridges the gap between what these systems have the potential to do with the breadth, depth, precision, and traceability that good research demands.

The Cato Institute has already begun creating AI-enhanced research capabilities. The Senior Research Engineer, Applied AI, joins that effort as Cato’s first dedicated engineering position focused on the research domain — a role with significant latitude to shape how research technology evolves at Cato.

The Senior Research Engineer closely partners with research teams, understanding their problems and identifying where AI and other advanced methods can make a real difference.

And the Senior Research Engineer gets their hands dirty, building state-of-the-art, research-grade tooling and capabilities — such as context engineering architectures, AI output benchmarking tools, and literature discovery systems.

Project priorities emerge through consultation between the Senior Research Engineer, the CTA, and research leadership — a process that will take shape as this new role matures, and the Senior Research Engineer will play an active part in shaping it.

The projected salary range for this role is $100,000 - $190,000 per year. 

Compensation is based on the successful candidate's educational background, experience, and skills.

About Cato

The Cato Institute is a public policy research organization — a think tank — dedicated to the principles of individual liberty, limited government, free markets, and peace. Its scholars and analysts conduct independent, nonpartisan research on a wide range of policy issues.

Founded in 1977, Cato owes its name to Cato’s Letters, a series of essays published in 18th-century England that presented a vision of a society free from excessive government power. Those essays inspired the architects of the American Revolution. And the simple, timeless principles of that revolution — individual liberty, limited government, and free markets — turn out to be even more powerful in today’s world of global markets and unprecedented access to information than Jefferson or Madison could have imagined. Social and economic freedom is not just the best policy for a free people, it is the indispensable framework for the future.

Cato Institute is an Equal Opportunity Employer.

Responsibilities

• Organize and support a cross-department working group to:

          -Identify opportunities for AI-enhanced research methods

          -Establish best practices, training materials, and reusable templates that help scholars leverage AI tools effectively

• Build research tools and multi-step AI workflows that improve how scholars work, iterating system architecture and integrations based on their feedback and usage
• Design and implement context engineering systems to structure Cato’s policy research for accurate retrieval and analysis by AI agents
• Evaluate AI outputs against scholarly standards, diagnosing whether poor results stem from context gaps, architectural flaws, or model limitations — and implement programmatic guardrails that enforce analytical rigor and empirical honesty
• Partner with scholars and data visualization specialists on the technical infrastructure of major reports

Likely Initial Focus Areas (First 6-12 Months)

• Launch the cross-department AI-enhanced research working group
• Discover existing research technology usage and workflows between multiple Cato research departments
• Devise and execute empirical assessment methods for custom AI instructions already in use
• Build tools and create technical organization to address opportunities identified by the working group and discovery

Requirements

Education and Experience

• Bachelor’s degree in computer science, data science, statistics, economics, computational social science, or a related quantitative or technical field
• 5+ years of experience building software, tools, or data systems, including experience in or serving research, policy, government, or academic environments
• Expertise building LLM-enabled systems (prompting, retrieval/context construction, tool use, and evaluation), and iterating them based on structured empirical evaluation
• Proficiency with multiple major LLMs: ChatGPT, Claude, Gemini, and/or Grok
• Proficiency with Python to build research tools and integrate AI capabilities
• Working knowledge of Claude Code, Codex, or