AI Infrastructure / Product Engineer at Clera

Job description

ABOUT THE ROLE Join a healthtech team building dependable AI products for legal work. You will work across AI research and product, creating the evaluations, services, and features that bring applied AI into production. WHAT YOU'LL DO - Build repeatable benchmarks and evaluation pipelines for model accuracy, hallucinations, retrieval quality, latency, and cost. - Create dashboards that help the team track changes in system performance. - Turn research prototypes into production retrieval, drafting, document, and agent workflows. - Develop backend services, APIs, and internal tools to support testing and releases. - Deploy and operate cloud infrastructure, including monitoring, databases, and delivery pipelines. - Partner with AI research while staying connected to product and user needs. WHAT WE'RE LOOKING FOR - At least 3 years of experience as a software, infrastructure, or product engineer building and deploying production systems. - Strong Python skills and hands-on cloud deployment experience. - Experience building evaluation pipelines, benchmarks, or assessment systems for machine learning or AI systems. - Experience with APIs, databases, backend services, deployment pipelines, monitoring, and reliable cloud operations. - Ability to turn experimental code and ambiguous ideas into usable, maintainable products, with experience designing dashboards or monitoring systems. - Interest or experience in LLMs, retrieval-augmented generation, agents, AI benchmarks, or document automation. Full-stack experience is a plus. - Helpful technologies include FastAPI, Docker, React, Next.js, Postgres, and vector databases. COMPENSATION & BENEFITS Annual base salary: $180,000 to $260,000 USD. Visa sponsorship is not available. LOCATION Remote, United States.

Requirements

Must-haves

Join a healthtech team building dependable AI products for legal work. You will work across AI research and product, creating the evaluations, services, and features that bring applied AI into production.
Build repeatable benchmarks and evaluation pipelines for model accuracy, hallucinations, retrieval quality, latency, and cost.
Create dashboards that help the team track changes in system performance.
Turn research prototypes into production retrieval, drafting, document, and agent workflows.
Develop backend services, APIs, and internal tools to support testing and releases.
Deploy and operate cloud infrastructure, including monitoring, databases, and delivery pipelines.
Partner with AI research while staying connected to product and user needs.
At least 3 years of experience as a software, infrastructure, or product engineer building and deploying production systems.
Strong Python skills and hands-on cloud deployment experience.
Experience building evaluation pipelines, benchmarks, or assessment systems for machine learning or AI systems.
Experience with APIs, databases, backend services, deployment pipelines, monitoring, and reliable cloud operations.
Ability to turn experimental code and ambiguous ideas into usable, maintainable products, with experience designing dashboards or monitoring systems.
Helpful technologies include FastAPI, Docker, React, Next.js, Postgres, and vector databases.
Remote, United States.

Nice-to-haves

Interest or experience in LLMs, retrieval-augmented generation, agents, AI benchmarks, or document automation. Full-stack experience is a plus.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aipythonmachine learningdockerreactnext.jspostgres

Platform: ashby
Effort: quick