Remote AI Operations Engineer

Jobgether; United States; Remote; USD 90,000 - 103,000; Full time

Benefits offered by this job

Remote work within US

Hourly pay: $65-$75

W-2 contract benefits

100% remote

Job summary

Jobgether is seeking an AI Operations Specialist based in the United States to transform manual QA into AI-powered workflows. You will identify automation opportunities, map current processes, and partner with product, legal, and engineering teams to implement reliable AI solutions with strong human oversight.

You will establish quality standards, develop evaluation datasets, and measure AI performance using accuracy, precision, recall, and sampling-based checks.

Qualifications

• 5-7 years of professional experience in operations, analytics, or AI-related fields.
• Hands-on with AI tools and building an AI-powered workflow.
• Experience measuring performance with accuracy, precision, recall, or related metrics.
• Ability to turn ambiguous processes into structured, repeatable workflows.
• Strong written and verbal communication for cross-functional teams.
• Willingness to learn new AI evaluation methods and tools.
• Technical degree not required; training provided.

Responsibilities

• Identify and prioritize AI automation opportunities based on business impact.
• Map workflows and determine tasks suitable for AI vs human review.
• Design, build, and monitor AI-powered workflows with quality controls.
• Establish quality standards and evaluate AI performance before deployment.
• Develop evaluation datasets and test cases; monitor model reliability.
• Collaborate with product, engineering, and legal to define launch readiness.
• Document processes and best practices for future deployments.

Skills

AI operations

Quality assurance

Process mapping

Data analysis

Stakeholder communication

Tools

SQL

Python

APIs

Job description

Jobgether is seeking an AI Operations Specialist based in the United States to transform manual QA into AI-powered workflows. You will identify automation opportunities, map current processes, and partner with product, legal, and engineering teams to implement reliable AI solutions with strong human oversight.

You will establish quality standards, develop evaluation datasets, and measure AI performance using accuracy, precision, recall, and sampling-based checks.