Sr. Director, AI Platform and Engineering

Department:

Job Description:

As the Sr. Director AI Platform and Engineering you will play a key role in supporting The Mutual Group (TMG) GuideOne Insurance and future members by leading the technical design engineering practices and execution required to turn TMGs AI-First IT vision into practical enterprise capability. This role is accountable for building reusable AI platforms architecture patterns engineering playbooks and delivery practices that enable AI adoption across business processes software delivery and IT operations.

This is a highly technical leadership role for a hands-on engineering leader who can operate across AI platforms application engineering automation data cloud integration security observability and modern software delivery. The Sr. Director will lead a small team of architects engineers contractors and system integration partners to build foundational capabilities and reusable assets that help TMG move from AI experimentation to production-grade implementation.

The role will work closely with Applications Engineering Infrastructure Operations Security Data Architecture business teams and AI & Technology Risk Governance to ensure AI capabilities are secure governed observable reliable cost-effective and ready to scale. The team is intended to serve as a catalyst creating platforms patterns and playbooks that broader IT and business teams can adopt over time.

Work Arrangement:

• Employees who live within 30 miles of the TMG home office are expected to follow a hybrid or in-office schedule. The initial training period may require additional inoffice days.

Accountabilities:

Platform Strategy & Technical Leadership

• Define and lead the technical roadmap for TMGs enterprise AI platform and AI engineering capabilities aligned to business priorities enterprise architecture security standards and governance expectations.

• Translate AI-First IT strategy into practical platform capabilities reference architectures engineering standards reusable components and delivery patterns.

• Evaluate AI platforms cloud services frameworks vendor solutions integration patterns and development tools with a focus on security reuse interoperability scalability maintainability and business value.

• Provide hands-on technical leadership in architecture reviews solution design technical decision-making delivery planning and complex problem-solving.

• Stay current on emerging AI engineering patterns GenAI platforms agent frameworks model orchestration enterprise knowledge systems and responsible deployment practices.

Business and Technology Enablement

• Partner with business and technology teams to design and deliver AI-enabled capabilities for underwriting claims operations finance customer service and other enterprise functions.

• Translate business use cases into scalable technical solutions including decision support workflow automation document intelligence knowledge retrieval summarization classification triage and productivity tools.

• Establish repeatable technical patterns for moving AI use cases from proof of concept to secure production-ready adoption.

• Work with product business data and risk partners to define solution feasibility data needs integration approach human oversight evaluation criteria and operational readiness.

• Build reusable accelerators and implementation playbooks that allow similar AI capabilities to be deployed across multiple business processes with less rework.

Architecture Engineering Standards & Platform Delivery

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

• Establish technical standards for model access prompt and response handling context management retrieval-augmented generation semantic search vector databases observability cost management and production support.

• Lead delivery of foundational AI platform capabilities such as model gateways model catalogs orchestration layers RAG frameworks vector stores embedding pipelines evaluation frameworks usage monitoring and governance controls.

• Establish patterns for integrating AI capabilities with enterprise systems APIs data platforms document repositories workflow tools service management platforms and business applications.

• Create reusable engineering assets templates reference implementations and deployment playbooks that improve delivery speed quality consistency and reuse.

GenAI Agentic AI & AI Engineering Practices

• Guide implementation of Generative AI solutions using LLMs SLMs embeddings prompt engineering RAG semantic search summarization classification extraction and enterprise knowledge retrieval.

• Define patterns for Agentic AI including tool and function calling workflow orchestration human-in-the-loop controls memory and context management guardrails monitoring and safe execution.

• Establish usage patterns for Model Context Protocol (MCP) or similar approaches for connecting AI systems to enterprise tools data sources APIs and workflow actions in a secure and governed manner.

• Guide AI-assisted engineering practices across coding testing documentation requirements analysis code review quality engineering and developer productivity.

• Collaborate with Infrastructure and IT Operations teams to apply AI to observability incident response root cause analysis predictive monitoring runbook automation service management and operational productivity.

Security Governance & Production Readiness

• Partner with the Senior Director AI & Technology Risk Governance Security Legal Compliance Data and Architecture teams to operationalize AI engineering governance.

• Embed secure-by-design and privacy-by-design principles into AI platform architecture data flows integrations engineering practices and production deployments.

• Define engineering controls for sensitive data handling identity and access management prompt and response logging output validation human oversight vendor integration and production readiness.

• Ensure AI platforms and applications are designed with appropriate logging monitoring traceability testing resilience access controls incident response and lifecycle management.

• Establish practices for model selection experimentation evaluation validation performance monitoring drift detection feedback loops cost optimization and responsible production deployment.

Team Leadership Delivery & Enterprise Enablement

• Lead and develop a high-performing technical team of architects engineers contractors and integration partners.

• Lead from the front by staying close to the work reviewing designs resolving technical issues and personally driving complex initiatives when needed.

• Own delivery across scope schedule quality risk dependencies technical readiness adoption and business value.

• Build communities of practice technical playbooks reference architectures and enablement materials that help broader IT teams adopt AI-First engineering practices over time.

• Create a culture of engineering excellence accountability curiosity disciplined experimentation documentation reuse security and continuous improvement.

Qualifications:

• 12 years of progressive technology experience including leadership responsibility for software engineering platform engineering architecture cloud data automation AI or enterprise technology delivery.

• 8 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 technical fluency across cloud platforms APIs microservices event-driven architecture data platforms DevSecOps CI/CD test automation observability cybersecurity identity and privacy.

• Proven experience delivering production-grade enterprise platforms reusable engineering frameworks integration patterns automation capabilities or developer productivity solutions.

• Experience working in regulated environments with strong security privacy risk compliance auditability and operational readiness expectations.

• Bachelors degree in Computer Science Engineering Information Systems Data Science or related field required. Masters degree preferred.

Leadership Attributes

• Deeply technical hands-on engineering leader who can guide architecture and personally drive complex problem-solving when needed.

• Practical platform and delivery leader with strong bias for reusable scalable secure and maintainable solutions.

• Strong analytical thinker who uses data metrics and root-cause analysis to improve engineering and operational outcomes.

• Collaborative partner who can work across business technology security data infrastructure architecture operations and governance teams.

• Strong delivery owner with disciplined planning clear decision-making and accountability for outcomes.

• Talent developer who raises engineering standards coaches teams and builds a culture of learning quality security and continuous improvement.

Pay Range:

Anticipated Hiring Range:

$190000 - $230000annual 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 Groupis 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.

• Know Your Rights: Workplace Discrimination is Illegal

• Your Rights Under USERRA

Applicants requiring a reasonable accommodation due to a disability at any stage of the employment application process should contact.

Employment Verification

The Mutual Group participates in theE-Verifyprogram 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 fromemployment discriminationbased 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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