Department:
Information Technology
Job Description:
As the Principal AI Engineering Architect, you will play a key role in supporting The Mutual Group (TMG), GuideOne Insurance, and future members by defining and guiding the technical architecture for AI-first engineering, secure AI platforms, reusable components, integration patterns, and scalable technical standards across TMG. This is a senior individual contributor role for a deeply technical architect who can translate complex business and technology needs into practical, secure, and reusable AI-enabled solutions.
This role will work across AI-First IT, Applications, Engineering, Data, Infrastructure, Operations, Security, Architecture, and business teams to design AI capabilities that can move from concept to production with the right architecture, controls, integration model, and operational readiness. The Principal AI Engineering Architect will be expected to stay close to the work, review designs, guide engineering teams, solve difficult technical problems, and create patterns that can be reused across multiple initiatives.
The role will have deeper focus on AI-enabled business processes and AI-first future platforms, while also supporting AI adoption across the IT SDLC and IT operations. The successful candidate will bring strong technical judgment, hands-on architecture depth, and the ability to simplify complex AI engineering concepts into standards, blueprints, and implementation guidance that broader teams can adopt.
Work Arrangement:
Accountabilities:
Architecture Strategy & Technical Direction
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.
AI Platform Architecture & Reusable Engineering Patterns
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.
Define integration patterns for connecting AI capabilities with enterprise systems, APIs, data platforms, document repositories, workflow tools, service management platforms, and business applications.
Create architecture blueprints, technical standards, reusable components, templates, and implementation guidance that improve speed, consistency, quality, and reuse.
Guide decisions on build versus buy, platform selection, vendor capabilities, interoperability, scalability, maintainability, and cost effectiveness.
Ensure AI platform patterns are designed for secure production use, including reliability, monitoring, access control, auditability, and lifecycle management.
GenAI, Agentic AI & Model Engineering
Guide implementation of Generative AI solutions using LLMs, SLMs, embeddings, prompt engineering, RAG, semantic search, summarization, classification, extraction, and enterprise knowledge retrieval.
Define technical patterns for Agentic AI, including tool and function calling, workflow orchestration, human-in-the-loop controls, context management, memory patterns, guardrails, monitoring, and safe execution.
Establish usage patterns for Model Context Protocol (MCP) or similar approaches for securely connecting AI systems to enterprise tools, data sources, APIs, and workflow actions.
Support practices for model selection, experimentation, evaluation, validation, performance monitoring, drift detection, feedback loops, and responsible production deployment.
Help engineering teams design AI solutions that are accurate, observable, explainable where appropriate, cost-aware, and aligned with business and risk expectations.
Business Solution Architecture & Enterprise Adoption
Partner with business, product, data, and technology teams to design AI-enabled solutions for underwriting, claims, operations, finance, customer service, and other enterprise functions.
Translate business needs into practical AI architectures for decision support, workflow automation, document intelligence, knowledge assistance, triage, summarization, and productivity improvement.
Help teams evaluate feasibility, data readiness, integration complexity, user experience, human oversight, and operational support requirements.
Create reusable patterns that allow similar AI capabilities to be deployed across multiple business processes with less rework.
Communicate architecture decisions clearly to technical and non-technical stakeholders, including tradeoffs, risks, dependencies, and implementation options.
Security, Governance & Engineering Quality
Partner with Security, Data, Architecture, and AI & Technology Risk Governance teams to embed secure-by-design, privacy-by-design, and responsible AI practices into solution architecture.
Define technical controls for identity and access management, sensitive data handling, prompt and response logging, output validation, human oversight, vendor integration, and production readiness.
Ensure AI solutions align with enterprise standards for security, privacy, auditability, observability, resilience, compliance, and operational support.
Participate in architecture governance, design reviews, technical risk assessments, and production readiness reviews.
Promote engineering quality through strong documentation, testability, traceability, performance considerations, and clear support models.
Qualifications:
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.
Leadership Attributes
Deeply technical architect who can dive into details while keeping architecture practical, scalable, and business aligned.
Strong systems thinker who simplifies complexity into reusable patterns, standards, and clear technical guidance.
Hands-on problem solver with strong analytical reasoning and sound judgment.
Collaborative partner who builds trust across business, engineering, data, security, infrastructure, operations, and governance teams.
Constructive challenger who raises technical standards while helping teams move quickly and responsibly.
Strong communicator who can explain complex AI and architecture concepts in clear, actionable terms.
Pay Range:
Anticipated Hiring Range:
$170,000 - $200, 000 annual base salary depending on experience, qualifications, and geographic location
Benefits:
We are proud to offer our full-time regular employees a robust benefits suite that includes:
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
Equal Opportunity Employer
The Mutual Group is an Equal Opportunity Employer. It is our policy to recruit, hire, train and promote individuals in all job classifications without regard to race, color, religion, sex, national origin, age, veteran status, disability, sexual orientation, gender identity or any other characteristic protected by law.
Applicants requiring a reasonable accommodation due to a disability at any stage of the employment application process should contact [email protected] .
Employment Verification
The Mutual Group participates in the E-Verify program and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. You are protected from employment discrimination based on your citizenship status and national origin.
E-Verify Program Overview
E-Verify Participation Poster
All offers of employment are contingent upon the successful completion of a background check.
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