AI Infrastructure / Product Engineer

Clera; United States; Remote; USD 180,000 - 260,000; Full time

Job summary

Clera is seeking a hands-on engineer at the intersection of AI research and product to turn promising AI experiments into dependable tools for legal work. You will own evaluation systems, backend services, and features that bring applied AI from prototype to production, shaping how quality is measured and improved across the team.

The role emphasizes building evaluation pipelines, dashboards, and production features for retrieval, drafting, document, and agent workflows, with a strong focus on

Qualifications

• 3+ 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 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.

Responsibilities

• Build repeatable benchmarks and evaluation pipelines measuring model accuracy, hallucinations, retrieval quality, latency, and cost.
• Create dashboards that visualize system performance for the team.
• Develop production features for retrieval, drafting, document, and agent workflows.
• Build backend services, APIs, and internal tools to test and release improvements quickly.
• Deploy and operate cloud infrastructure including monitoring, databases, delivery pipelines, and reliable operations.
• Work closely with AI research while aligning with product and user needs.

Skills

Python

Cloud deployment

Backend services

APIs

Databases

Dashboard design

ML/AI eval pipelines

LLMs / RAG

Full-stack

Tools

FastAPI

Docker

React/Next.js

Postgres

Vector databases

AI benchmarks

Document workflows

Job description

About the Role

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.

What You'll Do

• 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.

What We're Looking For

• 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.

Compensation & Benefits

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.

Location

Fully remote, open to candidates based in the United States only.