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You will build and maintain evaluation pipelines and backend services to transform AI research prototypes into production-grade tools. This role involves deploying cloud infrastructure and creating monitoring systems to ensure high performance and reliability for legal AI workflows.
This is a hands-on engineering role at the intersection of AI research and product, focused on turning promising AI experiments into dependable, production-grade tools for legal work. You will own the evaluation systems, backend services, and features that bring applied AI from prototype to reality, with direct influence over how quality is measured and improved across the team.
Build repeatable benchmarks and evaluation pipelines that measure model accuracy, hallucinations, retrieval quality, latency, and cost.
Create dashboards that make changes in system performance visible to the broader team.
Develop production features that transform research prototypes into usable retrieval, drafting, document, and agent workflows.
Build backend services, APIs, and internal tools that help the team test and release improvements quickly.
Deploy and operate cloud infrastructure including monitoring, databases, delivery pipelines, and reliable operations.
Work closely with AI research while staying connected to product and user needs.
3 or more years of experience as a software, infrastructure, or product engineer building and deploying production systems.
Strong Python skills and hands-on experience deploying software to the cloud.
Experience building evaluation pipelines, benchmarks, or assessment systems for machine learning or AI systems.
Solid background working with APIs, databases, backend services, and deployment pipelines.
A track record of converting research prototypes or experimental code into usable, maintainable products.
Experience designing dashboards or monitoring systems that surface system performance changes.
Interest in LLMs, retrieval-augmented generation, agents, and AI evaluation.
Full-stack experience spanning both frontend and backend is a plus.
Familiarity with FastAPI, Docker, React or Next.js, Postgres, vector databases, AI benchmarks, or document automation workflows is helpful.
Base salary: $180,000 to $260,000 USD annually, depending on relevant skills, experience, and role scope. Visa sponsorship is not available for this role.
Fully remote, open to candidates based in the United States only.
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