AI Infrastructure / Product Engineer

Clera

United States

Remote

Who this role is best for

Aimed at mid-to-senior-level engineers with cloud and AI deployment experience who can bridge research and product teams.

Best fit for

Candidates with 3+ years of production system deployment experience and cloud expertise
— “At least 3 years of experience as a software, infrastructure, or product engineer building and deploying production systems.”
Individuals who have experience developing evaluation pipelines for AI systems
— “Experience building evaluation pipelines, benchmarks, or assessment systems for machine learning or AI systems.”
Engineers with strong Python skills and interest in LLMs and document automation
— “Interest or experience in LLMs, retrieval-augmented generation, agents, AI benchmarks, or document automation.”

Things to consider

Remote work is limited to the United States, excluding international candidates
— “Remote within the United States.”
Visa sponsorship is not available, requiring candidates to be US-based
— “Visa sponsorship is not available.”

How to stand out

Highlight experience in deploying AI models and building evaluation tools in your resume and interviews
— “Build repeatable benchmarks and evaluation pipelines to measure model accuracy, hallucinations, retrieval quality, latency, and cost.”
Emphasize your ability to transform experimental code into production-ready systems
— “Ability to turn ambiguous ideas and experimental code into usable, maintainable products.”
Showcase your experience with cloud infrastructure and deployment pipelines
— “Deploy and operate cloud infrastructure, including monitoring, databases, delivery pipelines, and reliable operations.”
Demonstrate your skills in creating performance dashboards and backend services
— “Create dashboards that make changes in system performance visible to the team.”

Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

Developed repeatable benchmarks and evaluation pipelines
Created dashboards for system performance visibility
Developed production retrieval workflows
Deployed and operated cloud infrastructure

Typical background

3+ years of experience as a software, infrastructure, or product engineer

Skills & requirements

Required

PythonCloud DeploymentApisDatabasesBackend ServicesDeployment PipelinesProduction MonitoringEvaluation PipelinesBenchmarking

Preferred

FastapiDockerReactNext.jsPostgreSQLVector Databases

Stack & domain

PythonCloud DeploymentApisDatabasesBackend ServicesDeployment PipelinesProduction MonitoringEvaluation PipelinesBenchmarksAssessment SystemsLlmsRetrieval-augmented GenerationAgentsAI BenchmarksDocument AutomationFastapiDockerReactNext.jsPostgreSQLVector DatabasesLeadershipCommunicationHealthtechAI

About the role

Original posting from Clera via Ashby

ABOUT THE ROLE
As an AI Infrastructure / Product Engineer, you will work at the intersection of AI research and product development at a healthtech company building AI products. You will help turn experiments into dependable systems and features, and build ways to measure and improve their quality.
WHAT YOU'LL DO
Build repeatable benchmarks and evaluation pipelines to measure model accuracy, hallucinations, retrieval quality, latency, and cost.
Create dashboards that make changes in system performance visible to the team.
Develop production retrieval, drafting, document, and agent workflows from research prototypes.
Build backend services, APIs, and internal tools to help test and release improvements.
Deploy and operate cloud infrastructure, including monitoring, databases, delivery pipelines, and reliable operations.
Collaborate 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 with APIs, databases, backend services, deployment pipelines, and production monitoring.
Experience building evaluation pipelines, benchmarks, or assessment systems for machine learning or AI systems.
Ability to turn ambiguous ideas and experimental code into usable, maintainable products.
Interest or experience in LLMs, retrieval-augmented generation, agents, AI benchmarks, or document automation.
Full-stack experience is helpful. Familiarity with FastAPI, Docker, React, Next.js, Postgres, or vector databases is a plus.
COMPENSATION & BENEFITS
Annual base salary is $180,000 to $260,000 USD, depending on skills, experience, and role scope. Visa sponsorship is not available.
LOCATION
Remote within the United States.

Source: Clera careers (Ashby)