Principal AI Engineering Architect

The Mutual Group

. Define architecture patterns and technical standards for AI-enabled applications, copilots, intelligent workflows, automation agents, enterprise knowledge solutions, and reusable AI components.

Posted 5/17/2026full-timeIllinois, Iowa, Massachusetts, Texas, Washington • 🇺🇸 United StatesLead💰 $170,000 - $200,000 per yearWebsite

Tech Stack

Tools & technologies

CloudCyber SecurityMicroservices

About the role

Key responsibilities & impact

Define architecture patterns and technical standards for AI-enabled applications, copilots, intelligent workflows, automation agents, enterprise knowledge solutions, and reusable AI components.
Translate business and technology use cases into scalable solution architectures, including application design, data flows, integration patterns, model usage, security controls, and operational requirements.
Partner with the Sr. Director, AI Platform and Engineering to shape platform architecture, technical roadmaps, reference implementations, and engineering playbooks.
Provide hands-on architecture leadership in design reviews, technical decision-making, proof-of-concept evaluation, implementation planning, and production readiness.
Stay current on emerging AI engineering patterns, GenAI platforms, agent frameworks, model orchestration, cloud AI services, enterprise knowledge systems, and secure deployment practices.
Design reusable platform patterns for model access, retrieval-augmented generation, vector databases, semantic search, embeddings, enterprise knowledge integration, prompt and response handling, and AI observability.
Create architecture blueprints, technical standards, reusable components, templates, and implementation guidance that improve speed, consistency, quality, and reuse.

Requirements

What you’ll need

10+ years of progressive technology experience across software engineering, architecture, platform engineering, cloud, data, integration, automation, AI, or enterprise technology delivery.
5+ years of experience with AI, machine learning, automation, advanced analytics, intelligent platforms, developer productivity tools, or emerging technology capabilities.
Strong technical depth in Generative AI patterns, including LLMs, SLMs, embeddings, prompt engineering, RAG, vector databases, semantic search, evaluation frameworks, and enterprise knowledge integration.
Experience with Agentic AI patterns, including agents, tool/function calling, orchestration, human-in-the-loop workflows, context management, guardrails, monitoring, and safe deployment.
Familiarity with Model Context Protocol (MCP) or similar approaches for securely connecting AI systems to enterprise tools, data sources, APIs, and workflow actions.
Strong understanding of modern architecture patterns, including APIs, microservices, event-driven design, cloud-native platforms, data integration, DevSecOps, CI/CD, observability, cybersecurity, identity, and privacy.
Proven experience designing production-grade enterprise platforms, reusable architecture patterns, integration frameworks, automation capabilities, or developer productivity solutions.
Experience working in regulated environments with security, privacy, risk, compliance, auditability, and operational readiness expectations preferred.
Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or related field required.
Master’s degree preferred.

Benefits

Comp & perks

Competitive base salary plus incentive plans for eligible team members
401(K) retirement plan that includes a company match of up to 6% of your eligible salary
Free basic life and AD&D, long-term disability and short-term disability insurance
Medical, dental and vision plans to meet your unique healthcare needs
Wellness incentives
Generous time off program that includes personal, holiday and volunteer paid time off
Flexible work schedules and hybrid/remote options for eligible positions
Educational assistance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

AI-enabled applicationsGenerative AI patternsmachine learningautomationadvanced analyticsintegration frameworkscloud-native platformsDevSecOpsCI/CDobservability

Soft Skills

architecture leadershiptechnical decision-makingcollaborationcommunicationproblem-solvingdesign reviewsimplementation planningproduction readinessevaluation frameworkscontext management

Certifications

Bachelor’s degree in Computer ScienceBachelor’s degree in EngineeringBachelor’s degree in Information SystemsBachelor’s degree in Data ScienceMaster’s degree