AI Solutions Engineer

Arthur Imaging; San Gabriel (CA); On-site; USD 120,000 - 170,000; Full time

Job summary

Arthur Imaging seeks a hands-on AI workflow engineer to turn fragmented knowledge into reliable AI-assisted systems. You will learn the product, data, and operations data, then build internal knowledge tools and automations that save measurable time.

The role emphasizes practical delivery over demos, with a focus on safe, testable workflows grounded in company information and accessible for daily use.

Qualifications

• Hands-on experience building AI-assisted applications or data workflows used by real teams.
• Strong knowledge of APIs, structured data, retrieval systems, evaluation and prompt design.
• Ability to work with imperfect business data and turn ambiguous needs into testable solutions.

Responsibilities

• Map existing workflows with sales, ecommerce, product-data, service and operations teams; convert vague requests into clear and testable specifications.
• Audit, clean and organize the source data required for reliable AI workflows, including product information, service knowledge and internal documentation.
• Design retrieval-based knowledge tools that answer questions from approved company sources and provide traceable references.
• Build automations and lightweight integrations using APIs, webhooks, scripts or workflow platforms to reduce repetitive manual work.
• Create evaluation sets and acceptance criteria; measure accuracy, failure cases, time saved and operational value before release.
• Design safeguards for hallucination, prompt injection, sensitive information, access controls and human review.
• Monitor model usage, latency and cost; select the simplest technical approach that meets the quality requirement.
• Document architecture, prompts, data sources, limitations, maintenance procedures and user instructions.
• Pilot customer-facing AI workflows only after internal testing, with clearly defined scope, ownership and escalation paths.

Skills

AI product development

APIs & data workflows

Prompt design

Data privacy & governance

Documentation

Workflow platforms

RAG techniques

Vector search

Tools

RAG techniques

Vector search

API integration

Job description

Wholesale purchasing available for businesses, schools, government, and nonprofits

Local managed print support within 50 miles of 91776

Southern California Applied AI and process improvement

What we’re looking for

• Hands-on experience building AI-assisted applications, automations or data workflows used by real teams.
• Strong practical knowledge of APIs, structured data, retrieval systems, evaluation and prompt design.
• Ability to work with imperfect business data and turn ambiguous needs into testable solutions.
• Clear documentation habits and a thoughtful approach to privacy, access controls and human review.

Preferred qualifications

• Experience with ecommerce, product information, CRM, customer support or service operations.
• Familiarity with RAG, vector search, workflow platforms and lightweight web application development.
• Ability to explain technical tradeoffs clearly to non-technical colleagues.

What success looks like

Reliable tools that employees actually use, measurable time savings, documented limitations and a maintainable path from pilot to daily operation.

The opportunity

This is an applied, hands‑on role for someone who wants to turn fragmented knowledge and repetitive work into reliable AI‑assisted systems. You will begin by learning Arthur Imaging’s product, customer and operational data, then build internal knowledge tools and automations that save measurable time. The goal is not AI demos or pure research; it is useful workflows that are grounded in company information, tested against real examples and safe enough for daily use.

Key responsibilities

• Map existing workflows with sales, ecommerce, product‑data, service and operations teams; convert vague requests into clear and testable specifications.
• Audit, clean and organize the source data required for reliable AI workflows, including product information, service knowledge and internal documentation.
• Design retrieval‑based knowledge tools that answer questions from approved company sources and provide traceable references.
• Build automations and lightweight integrations using APIs, webhooks, scripts or workflow platforms to reduce repetitive manual work.
• Create evaluation sets and acceptance criteria; measure accuracy, failure cases, time saved and operational value before release.
• Design safeguards for hallucination, prompt injection, sensitive information, access controls and human review.
• Monitor model usage, latency and cost; select the simplest technical approach that meets the quality requirement.
• Document architecture, prompts, data sources, limitations, maintenance procedures and user instructions.
• Pilot customer‑facing AI workflows only after internal testing, with clearly defined scope, ownership and escalation paths.