Senior Director, AI Platform and Engineering

The Mutual Group

. Define and lead the technical roadmap for TMG’s enterprise AI platform and AI engineering capabilities, aligned to business priorities, enterprise architecture, security standards, and governance expectations.

Posted 5/17/2026full-timeDallas • Illinois, Iowa, Massachusetts, Texas, Washington • 🇺🇸 United StatesSenior💰 $190,000 - $230,000 per yearWebsite

Tech Stack

Tools & technologies

CloudCyber SecurityMicroservices

About the role

Key responsibilities & impact

Define and lead the technical roadmap for TMG’s 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.
Partner with business and technology teams to design and deliver AI-enabled capabilities for underwriting, claims, operations, finance, customer service, and other enterprise functions.
Establish repeatable technical patterns for moving AI use cases from proof of concept to secure, production-ready adoption.
Build reusable accelerators and implementation playbooks that allow similar AI capabilities to be deployed across multiple business processes with less rework.
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.
Guide implementation of Generative AI solutions using LLMs, SLMs, embeddings, prompt engineering, RAG, semantic search, summarization, classification, extraction, and enterprise knowledge retrieval.
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.

Requirements

What you’ll need

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.
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

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI engineeringGenerative AILLMsSLMsembeddingsprompt engineeringRAGvector databasessemantic searchevaluation frameworks

Soft Skills

technical leadershipproblem-solvingcollaborationcommunicationdelivery planningdecision-makingorganizational skillsstrategic thinkingadaptabilitymentorship

Certifications

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