AI Engineer

Mutual Of Enumclaw Insurance Holding Company; Seattle (WA); On-site; USD 149,000 - 173,000; Full time

Job summary

Mutual of Enumclaw seeks an AI Engineer to integrate vendor AI into underwriting, claims, and agent workflows. You won't build models from scratch; you'll connect Azure AI / AWS Bedrock to MOE data and core systems, ground them in our documents, test rigorously, and keep them safe in production.

As MOE's first dedicated AI Engineer, you'll bridge between tools and business results, aligning AI with governance and risk controls while delivering measurable efficiency gains.

Qualifications

• BS in CS or software engineering, or equivalent experience.
• 4-6+ years in software engineering with 1-2+ years in AI services.
• Strong Python skills and API/cloud experience.
• Experience with retrieval-augmented generation and vector search.
• Experience testing AI outputs for accuracy and safety.
• Understanding AI risks and data leakage controls.
• Clear communication with technical and business partners.

Responsibilities

• Integrate AI into insurance workflows via APIs.
• Deliver first AI use cases like underwriting intake and claims summarization.
• Ground AI in MOE knowledge with retrieval-augmented generation.
• Build evaluation tests for accuracy and safety.
• Implement guardrails and data protection measures.
• Monitor live AI solutions for quality and cost.
• Collaborate with underwriting, claims, and agents to translate problems into AI solutions.

Skills

Python

APIs

System integration

Cloud services

RAG

Vector search

Prompt design

AI testing

AI risks

Communication

Education

Bachelor's degree in CS/Software Eng

Tools

Azure AI

AWS Bedrock

Job description

Overview

Founded in 1898, Mutual of Enumclaw is a people-first insurer rooted in community, recognized as Washington's Best Company to Work For for the 14th consecutive year, and proudly serving individuals, families, farms, and businesses through local independent agents across the West.

The AI Engineer turns AI tools into working, trustworthy solutions inside MOE's underwriting, claims, and agent workflows. You won't build models from scratch. You'll connect vendor AI platforms and foundation models to MOE's data and core systems, ground them in our documents, test them rigorously, and keep them safe in production.

MOE takes a buy-first approach to AI. As our first dedicated AI Engineer, you'll be the in-house bridge between vendor tools and real business results, so MOE doesn't depend on consultants for every integration or change.

Location: Onsite - Seattle, WA

Hiring Range: $148,600 - $161,900*

Salary Range:$148,600 - $172,700

*The Hiring Range represents Mutual of Enumclaw's current hiring pay scale for this role. Mutual of Enumclaw reserves the right to modify or update this range any time. Exact compensation may vary based on skills and experience. Compensation is only one part of our entire total rewards package. To see some of the benefits and perks we offer, please click here.

Responsibilities

Integrate AI Into Insurance Workflows

• Connect vendor AI platforms and foundation models (through services such as Azure AI or AWS Bedrock) to MOE's policy, claims, billing, and agent systems using APIs.
• Deliver MOE's first AI use cases, such as underwriting submission intake, claims intake and summarization, and assistants for agents and employees.
• Configure and extend vendor AI tools so they fit how MOE actually works, rather than changing workflows to fit the tool.

Ground AI in MOE's Knowledge

• Build retrieval-augmented generation (RAG) so AI answers from MOE's underwriting guidelines, policy forms, procedures, and claims documents.
• Partner with data engineering to prepare, structure, and maintain the content and data that AI relies on.

Test and Evaluate

• Build evaluation tests that measure accuracy, consistency, and safety before launch and after every vendor model update.
• Work with underwriting and claims experts to define what a correct answer looks like and to review AI outputs.

Guardrails and Responsible AI

• Implement controls that protect personal and policyholder data, block off-limits responses, and route uncertain cases to a person.
• Log AI inputs, outputs, and decisions to support audit and regulatory review, working with the AI Governance lead.
• Apply MOE's AI governance standards and help shape them from hands-on experience.

Operate and Improve

• Monitor live AI solutions for quality, response time, and cost, and fix issues quickly.
• Retest and adjust solutions when vendors release new model versions.
• Document solutions so others can support and extend them.

Partner and Enable

• Translate business problems from underwriting, claims, and agency teams into practical AI solutions.
• Evaluate vendor AI capabilities technically and advise on build, buy, or configure decisions.
• Coach IT colleagues on AI engineering practices as MOE builds this capability.

Qualifications

Required

• Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent experience.
• 4-6+ years of software engineering experience, including 1-2+ years building applications with large language models or other AI services.
• Strong Python skills and experience with APIs, system integration, and cloud services.
• Hands-on experience with retrieval-augmented generation, vector search, and prompt design.
• Experience testing and evaluating AI outputs for accuracy and safety.
• Understanding of AI risks, including hallucinations, bias, and data leakage, and how to control them.
• Clear communication with both technical and business partners.

Preferred

• Insurance or financial services experience, especially in underwriting or claims.
• Experience with Azure AI / AWS Bedrock and with configuring enterprise AI platforms.
• Experience with document processing, such as extracting data from PDFs, emails, and forms.
• Experience working in a regulated environment with audit and compliance requirements.

Nice to Have

• Experience with agentic AI frameworks and multi-step workflows.
• Familiarity with insurance core platforms such as Guidewire or Duck Creek.
• Cloud or AI certifications.

What Success Looks Like in the First 12 Months

• 1-2 vendor AI use cases integrated and live in production, such as underwriting submission intake or claims summarization.
• An evaluation test suite in place for every live AI solution, rerun with each vendor model update.
• Guardrails and audit logging that meet MOE's AI governance standards.
• A reusable integration and RAG pattern that speeds up future AI use cases.
• Measurable business results tracked for each solution, such as time saved or cycle time reduced.