AI Application Development Manager

Arthur J. Gallagher · Cincinnati

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Welcome to Gallagher - a global community of people who bring bold ideas, deep expertise, and a shared commitment to doing what’s right. We help clients navigate complexity with confidence by empowering businesses, communities, and individuals to thrive. At Gallagher, you’ll find more than a job; you’ll find a culture built on trust, driven by collaboration, and sustained by the belief that we’re better together. Whether you join us in a client-facing role or as part of our brokerage division, our benefits and HR consulting division, or our corporate team, you’ll have the opportunity to grow your career, make an impact, and be part of something bigger. Experience a workplace where you’re encouraged to be yourself, supported to succeed, and inspired to keep learning. That’s what it means to live The Gallagher Way.

The AI Application Development Manager leads the team of developers who design, build, and maintain AJ Gallagher's AI applications — RAG pipelines, AI agents, and Copilot integrations delivered on our Microsoft Azure cloud stack. Reporting to the Director of AI Technology, you will own the day-to-day management of a team of AI Developers: setting priorities, coaching engineers of varying experience, and making sure the team ships reliable, production-grade software on schedule. You will build and maintain relationships with business stakeholders across Gallagher to understand their priorities and translate them into a delivery plan, while working within the architecture and technical standards set by the Senior AI Engineering Leads and Solution Architects. You won't be the one writing the code day to day, but you need enough fluency in AI/GenAI concepts (RAG, agents, LLMs, evaluations) and Azure infrastructure - to evaluate trade-offs, ask sharp questions, and represent your team credibly in an environment where governance and reliability matter as much as speed.

• Lead and Develop the AI Development Team: Manage the day-to-day work of a team of AI Developers building AI systems — assigning work, coaching engineers of varying experience levels, and owning performance management for the team.
• Own Business Stakeholder Relationships: Develop and maintain relationships with business stakeholders across Gallagher to understand their priorities, then translate those priorities into a concrete plan for the team.
• Plan and Deliver AI Initiatives: Produce detailed project schedules and resource plans with project managers and manage the team's roadmap so that AI initiatives ship on time and within scope.
• Direct Delivery Within the Team's Technical Standards: Ensure the team's day-to-day build work follows the architecture, patterns, and engineering standards set by the Senior AI Engineering Lead, coordinating integration across components and modules and holding the team to the team's quality bar.
• Own Production Support for AI Applications: Be accountable for the reliability and support of every AI application and agent already in production – new features, upgrades, incident responses.
• Manage Releases and Deployments: Oversee the release and deployment process for the team's AI solutions through the team's Azure DevOps CI/CD pipelines, working with engineering to keep deployments predictable and low-risk.
• Troubleshoot and Escalate Complex Issues: Operationally troubleshoot complex production issues alongside the team, and know when to pull in the Senior AI Engineering Lead or architects for issues that require a deeper technical fix.
• Ensure Governance, Compliance, and Business Continuity: Hold the team accountable to AJ Gallagher's IT policy and responsible AI requirements - Entra ID/RBAC, audit logging, human-in-the-loop checkpoints - and develop and maintain documented standards of built systems.
• Communicate Up and Across: Give the Director of AI Technology an accurate, current picture of delivery status and risk, and translate technical trade-offs into terms business stakeholders and executives can act on.

• Experience: 7-10+ years of professional software engineering experience, including at least 2 years working on AI/GenAI or ML-integrated systems (production RAG pipelines, agents, or LLM-powered applications).
• People Leadership: 3-5+ years directly leading or managing a team of software developers, including hiring, coaching, and performance management.
• Education: Bachelor's degree in Computer Science, Information Systems, or a related field, or equivalent practical experience.
• Technical Credibility: Competent to evaluate technical work at a high level across both AI/ML and traditional application development — enough to review architecture decisions, unblock the team, and hold a credible technical conversation with engineers, even though this is not a hands-on coding role.
• Delivery Management: Demonstrated experience producing detailed project schedules and resource plans, and delivering complex technical initiatives on time.
• Communication: Exceptional verbal and written communication skills, with the ability to speak and write comfortably to C-level audiences as well as technical staff.

Preferred Qualifications

• AI Ecosystem Familiarity: Practical familiarity with Azure AI Foundry, Azure OpenAI Service, Microsoft Copilot Studio, RAG architectures, or agent frameworks (Semantic Kernel, Microsoft Agent Framework, Langchain) - enough to critically evaluate the team's technical output. Critical to understand Azure resources and where AI fits within that landscape.
• .NET/Azure Background: Prior hands-on experience with C#/.NET/object-oriented programming and Azure application development, even if this role doesn't require writing production code day to day.
• Regulated Industry Experience: Experience in insurance, financial services, or another regulated industry, with familiarity with model risk management, NAIC AI compliance, or Sarbanes-Oxley-type controls.
• Azure DevOps / CICD: Experience with Azure DevOps repositories, boards, and pipelines, plus automated build/deployment tooling.
• Service Management: Experience partnering with support or service-desk functions (e.g., an AI Support Manager) on incident response and escalation paths.

Core Competencies

• People-First Leadership: Genuinely invested in growing engineers of varying experience levels; gives clear, actionable coaching and makes fair calls on hiring and performance.
• Stakeholder Trust-Builder: Earns credibility with business stakeholders by listening well and consistently translating their priorities into delivered work.
• Organized Delivery Owner: Keeps multiple concurrent initiatives, deadlines, and production commitments under control without letting anything slip.
• Calm Under Pressure: Stays effective during incidents, release windows, and conflicting deadlines, and keeps the team focused rather than reactive.
• Clear Communicator: Moves fluidly between technical detail for engineers and business-friendly framing for executives.
• Curious About AI: Stays current enough on AI, agents, and LLM concepts to ask sharp diagnostic and architectural questions, even without writing the code.

At Gallagher, we believe supporting our colleagues goes far beyond the role itself. For more information, visit our Benefits page.

• Competitive compensation
• Comprehensive benefits programs designed to support your well-being 
• Career development opportunities and ongoing learning 
• A collaborative, people-first culture with accessible leadership 
• The opportunity to do meaningful work with global reach and local impact 

At Gallagher, we are dedicated to building an inclusive and authentic workplace. If your past experience doesn’t align perfectly, we encourage you to join our Talent Community to stay connected to additional career opportunities. At times, we will consider transferable skills from previous roles.

Gallagher is an affirmative action/equal opportunity employer (Minorities/Females/Veterans/Disabled)

• Lead and Develop the AI Development Team: Manage the day-to-day work of a team of AI Developers building AI systems — assigning work, coaching engineers of varying experience levels, and owning performance management for the team.
• Own Business Stakeholder Relationships: Develop and maintain relationships with business stakeholders across Gallagher to understand their priorities, then translate those priorities into a concrete plan for the team.
• Plan and Deliver AI Initiatives: Produce detailed project schedules and resource plans with project managers and manage the team's roadmap so that AI initiatives ship on time and within scope.
• Direct Delivery Within the Team's Technical Standards: Ensure the team's day-to-day build work follows the architecture, patterns, and engineering standards set by the Senior AI Engineering Lead, coordinating integration across components and modules and holding the team to the team's quality bar.
• Own Production Support for AI Applications: Be accountable for the reliability and support of every AI application and agent already in production – new features, upgrades, incident responses.
• Manage Releases and Deployments: Oversee the release and deployment process for the team's AI solutions through the team's Azure DevOps CI/CD pipelines, working with engineering to keep deployments predictable and low-risk.
• Troubleshoot and Escalate Complex Issues: Operationally troubleshoot complex production issues alongside the team, and know when to pull in the Senior AI Engineering Lead or architects for issues that require a deeper technical fix.
• Ensure Governance, Compliance, and Business Continuity: Hold the team accountable to AJ Gallagher's IT policy and responsible AI requirements - Entra ID/RBAC, audit logging, human-in-the-loop checkpoints - and develop and maintain documented standards of built systems.
• Communicate Up and Across: Give the Director of AI Technology an accurate, current picture of delivery status and risk, and translate technical trade-offs into terms business stakeholders and executives can act on.

• Experience: 7-10+ years of professional software engineering experience, including at least 2 years working on AI/GenAI or ML-integrated systems (production RAG pipelines, agents, or LLM-powered applications).
• People Leadership: 3-5+ years directly leading or managing a team of software developers, including hiring, coaching, and performance management.
• Education: Bachelor's degree in Computer Science, Information Systems, or a related field, or equivalent practical experience.
• Technical Credibility: Competent to evaluate technical work at a high level across both AI/ML and traditional application development — enough to review architecture decisions, unblock the team, and hold a credible technical conversation with engineers, even though this is not a hands-on coding role.
• Delivery Management: Demonstrated experience producing detailed project schedules and resource plans, and delivering complex technical initiatives on time.
• Communication: Exceptional verbal and written communication skills, with the ability to speak and write comfortably to C-level audiences as well as technical staff.

Preferred Qualifications

• AI Ecosystem Familiarity: Practical familiarity with Azure AI Foundry, Azure OpenAI Service, Microsoft Copilot Studio, RAG architectures, or agent frameworks (Semantic Kernel, Microsoft Agent Framework, Langchain) - enough to critically evaluate the team's technical output. Critical to understand Azure resources and where AI fits within that landscape.
• .NET/Azure Background: Prior hands-on experience with C#/.NET/object-oriented programming and Azure application development, even if this role doesn't require writing production code day to day.
• Regulated Industry Experience: Experience in insurance, financial services, or another regulated industry, with familiarity with model risk management, NAIC AI compliance, or Sarbanes-Oxley-type controls.
• Azure DevOps / CICD: Experience with Azure DevOps repositories, boards, and pipelines, plus automated build/deployment tooling.
• Service Management: Experience partnering with support or service-desk functions (e.g., an AI Support Manager) on incident response and escalation paths.

Core Competencies

• People-First Leadership: Genuinely invested in growing engineers of varying experience levels; gives clear, actionable coaching and makes fair calls on hiring and performance.
• Stakeholder Trust-Builder: Earns credibility with business stakeholders by listening well and consistently translating their priorities into delivered work.
• Organized Delivery Owner: Keeps multiple concurrent initiatives, deadlines, and production commitments under control without letting anything slip.
• Calm Under Pressure: Stays effective during incidents, release windows, and conflicting deadlines, and keeps the team focused rather than reactive.
• Clear Communicator: Moves fluidly between technical detail for engineers and business-friendly framing for executives.
• Curious About AI: Stays current enough on AI, agents, and LLM concepts to ask sharp diagnostic and architectural questions, even without writing the code.

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