AI Operations & Workflow Optimizer

HistoryIT; Portland (ME); On-site; USD 70,000 - 120,000; Full time

Job summary

HistoryIT is seeking an AI Operations Analyst to help redesign and operationalize AI-assisted production systems within archival workflows. The role focuses on evaluating, documenting, testing, and improving processes across the company, not coding.

You will collaborate with leadership, services, and software teams to identify bottlenecks, measure results, and implement repeatable solutions that increase efficiency and quality in handling digital assets and research data.

Qualifications

• Strong understanding of AI tools and modern AI workflows.
• Exceptional systems-thinking and problem-solving abilities.
• Experience analyzing, improving, documenting, or managing processes.
• Strong organizational skills and attention to detail.
• Comfort working with data, spreadsheets, and structured information.
• Ability to learn complex workflows quickly.
• Ability to work independently in a fast-moving environment.
• Bachelor’s degree in Business, Computer Science, Information Systems, Data Analytics, or Engineering.

Responsibilities

• Learn and understand HistoryIT’s production workflows.
• Improve AI-assisted operations by evaluating outputs and testing prompts and workflows.
• Build and document workflows; develop SOPs and training materials.
• Collaborate with Services, Software Development, and Leadership teams to implement improvements.

Skills

AI tools

Systems thinking

Process analysis

Data handling

Independent work

Education

Bachelor’s degree in Business, CS, IS, Data Analytics, or Engineering

Tools

Workflow automation

Documentation tools

Job description

HistoryIT is seeking an AI Operations Analyst to help redesign and operationalize AI-assisted production systems within archival workflows. The role focuses on evaluating, documenting, testing, and improving processes across the company, not coding.

You will collaborate with leadership, services, and software teams to identify bottlenecks, measure results, and implement repeatable solutions that increase efficiency and quality in handling digital assets and research data.