Principal AI Engineering Architect

Job Summary

The Principal AI Engineering Architect will define and guide the technical architecture for AI-first engineering, secure AI platforms, reusable components, integration patterns, and scalable technical standards across The Mutual Group (TMG).

About the Role

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.

Responsibilities

• 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 integration patterns for connecting AI capabilities with enterprise systems, APIs, data platforms, document repositories, workflow tools, service management platforms, and business applications.
• 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.
• 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.
• Partner with business, product, data, and technology teams to design AI-enabled solutions for underwriting, claims, operations, finance, customer service, and other enterprise functions.
• 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.
• Work 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.

Qualifications

• 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
• Education 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.