Senior AI Engineer in Mundelein

• 7+ years of software or automation engineering, including 3+ years building and shipping applications backed by large models to production \n

• Direct, recent, hands-on experience building and publishing Claude skills or plug-ins. Broad experience with large models or frameworks, without shipped skills and plug-ins, is not sufficient. \n

• Demonstrated technical leadership as an individual contributor: setting standards other engineers followed, reviewing others’ architecture and code, and mentoring engineers without managing them \n

• Strong Python, REST APIs, and enterprise integration, with sound fundamentals in testing, version control, and monitoring \n

• Hands-on experience with foundational models: system and prompt design, skill and tool building, function and tool calling \n

• Retrieval-augmented , embeddings, and vector stores, including chunking and reranking \n

• Evaluation and monitoring for systems backed by large models, with a working feel for cost, latency, and reliability tradeoffs \n

• Experience operating inside a regulated enterprise, with security, governance, and access control as part of normal delivery \n

• Cloud experience (Azure or GCP / Vertex AI) \n

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related technical field, or equivalent practical experience \n

• Build reusable skills, package them as plug-ins, and compose them into governed AI applications used across HUB business lines \n

• Configure and tune foundational models for HUB use cases, including system and prompt design \n

• Build retrieval-augmented , embeddings, vector store, and multi-step workflow implementations over governed enterprise data \n

• Take business-built AI prototypes and productionize them into reliable, governed applications \n

• Own the engineering decisions behind cost, latency, and reliability tradeoffs across the AI estate \n

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Set the Technical Standard

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• Define and document the engineering standards the function builds to, covering architecture patterns, testing, logging, documentation, and release discipline \n

• Review architecture and code across the team, and raise the quality of what ships through that review \n

• Mentor AI Engineers and contract engineers, deliberately transferring knowledge so the function does not depend on any one person \n

• Set and uphold the enterprise standards and governance for skills, plug-ins, and MCP wherever they are used across HUB, on any surface, including builds executed by other engineering teams \n

• Partner with Enterprise Engineering on deep builds, defining the standard those builds must meet before they return to the catalog \n

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Own the AI Asset Platform

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• Own the technical operation of the skill and plug-in marketplace and the MCP catalog: intake, publish, version, maintain, and deprecate \n

• Apply access control, least-privilege, and audit to AI assets, partnering with Security, Privacy, and Cloud on and credentials \n

• Ensure every AI asset published to the enterprise has a defined owner, documented behavior, and a support path \n

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Quality, Evaluation, and Governance

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• Stand up and own evaluation harnesses, golden-set testing, guardrails, monitoring, and logging so AI output is consistent and reliable at enterprise scale \n

• Establish acceptance criteria and regression gating so a change that fixes one case does not silently break others \n

• Provide production support for the skills, plug-ins, and applications the function releases, including incident response for non-deterministic systems \n

• Translate governance, security, privacy, and regulatory requirements into engineering controls and audit-ready evidence \n

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Collaboration and Delivery

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• Partner with business stakeholders and the product function to turn prototyped ideas into production-ready, governed capabilities \n

• Partner with Enterprise Engineering, Data and Analytics, Cloud, and Security to ship reliably and route deep builds appropriately \n

• Represent AI Engineering in technical and governance forums \n

• Work within Agile ceremonies and document skills, applications, and technical decisions for handoff, audit, and maintenance \n

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• Agent development and orchestration (LangGraph, CrewAI, Claude Agent SDK), the growth path for this role \n

• Model Context Protocol design, MCP server governance, and agent-to-agent patterns \n

• and access concepts: RBAC, non-human or agent , and least privilege \n

• Working fluency in an AI governance framework such as the NIST AI Risk Management Framework, ISO/IEC 42001, or the NAIC model bulletin on insurer use of AI systems \n

• Experience as the senior technical voice in a new or maturing capability, including standing up standards where none existed \n

• UiPath or Microsoft Power Platform exposure, given the automation estate this function supports \n

• Insurance or financial services industry experience, and familiarity with audit and control expectations in a pre-IPO or public company environment \n

• Familiarity with Git, CI/CD pipelines, and modern software engineering practices, and tools such as Jira or Azure DevOps \n

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Key Competencies

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• Genuine software engineering depth rather than prompt-only development \n

• Influence without authority. This role sets standards for engineers who do not report to it, including engineers on other teams. \n

• Systems thinking, designing for consistency, resilience, and enterprise scale \n

• Willingness to do the unglamorous work: documentation, evaluation harnesses, access reviews, and production support \n

• Coaching instinct, with evidence of raising the level of engineers around them \n

• Clear technical communication with engineers, business stakeholders, and executive audiences \n

• Accountability and ownership for quality, stability, governance, and delivery \n

• Curiosity and adaptability as the AI stack evolves toward agents \n

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JOIN OUR TEAM

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Do you believe in the power of innovation, collaboration, and transformation? Do you thrive in a supportive and client focused work environment? Are you looking for an opportunity to help build and drive change in a rapidly growing and evolving organization? When you join HUB International, you will be part of a community of learners and doers focused on our Core Values: entrepreneurship, teamwork, integrity, accountability, and service.

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The expected salary range for this position is $ 130,000 to $170,000 and will be impacted by factors such as the successful candidate’s skills, experience and working location, as well as the specific position’s business line, scope and level. HUB International is proud to offer comprehensive benefit and total compensation packages which could include health/dental/vision/life/ insurance, FSA, HAS and 401(k) accounts, paid-time-off benefits such as vacation, sick, personal, floating holidays and company holidays. In addition, eligible annual bonuses, equity and commissions may be available for some positions.

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At HUB International, we are a team of entrepreneurs. We believe in protecting and supporting the aspirations of individuals, families, and businesses. We help our clients evaluate their risks and develop solutions tailored to their needs. We believe in empowering our employees to learn, grow, and make a difference. Our structure enables our teams to maintain their own unique, regional culture while leveraging support and resources from our corporate centers of excellence.

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HUB is a global insurance and employee benefits broker, providing a boundaryless array of business insurance, employee benefits, risk services, personal insurance, retirement, and private wealth management products and services. With over $5 billion in revenue and almost 20,000 employees in 600 offices throughout North America, HUB has grown substantially, in part due to our industry leading success in mergers and acquisitions., HUB is seeking a Senior AI Engineer to serve as the senior technical individual contributor for the AI Engineering function within our centralized technology organization, part of HUB’s AI & Automation organization. This is the most senior hands-on engineering seat in the function. The role builds the hardest work, sets the technical standards the rest of the team builds to, and owns the enterprise standards and governance for HUB’s skills, plug-ins, and MCP connections wherever they are used across HUB.

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This is an individual contributor role. It carries no direct reports. It does carry technical authority, and the person in it is expected to lead through standards, architecture, code review, and mentoring rather than through reporting lines. A significant portion of that influence extends to engineers outside the function, including builds executed by other engineering teams to the standard this role sets.

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The role builds on the Claude AI platform: creating reusable skills and plug-ins, composing them into governed AI applications, standing up retrieval over governed enterprise data, and professionalizing experimental prototypes into governed, tested, enterprise-ready applications. HUB runs Claude as its primary model today and the stack is expected to evolve toward agentic systems. Where a build requires deep engineering, such as net-new backend, new infrastructure, or complex integration, Enterprise Engineering executes it to the standard this role sets and returns it to the catalog to be governed and published. This role does not build or host foundational models and does not perform core machine learning or model training.