AI Application Development Manager

Gallagher•Rolling Meadows, IL

About The Position

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.

Requirements

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).
3-5+ years directly leading or managing a team of software developers, including hiring, coaching, and performance management.
Bachelor's degree in Computer Science, Information Systems, or a related field, or equivalent practical experience.
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.
Demonstrated experience producing detailed project schedules and resource plans, and delivering complex technical initiatives on time.
Exceptional verbal and written communication skills, with the ability to speak and write comfortably to C-level audiences as well as technical staff.

Nice To Haves

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.
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.
Experience in insurance, financial services, or another regulated industry, with familiarity with model risk management, NAIC AI compliance, or Sarbanes-Oxley-type controls.
Experience with Azure DevOps repositories, boards, and pipelines, plus automated build/deployment tooling.
Experience partnering with support or service-desk functions (e.g., an AI Support Manager) on incident response and escalation paths.

Responsibilities

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.