Senior AI Engineer

HUB International • Chicago, IL

5d • $130,000 - $190,000 • Hybrid

About The Position

HUB International is seeking a Senior AI Engineer to serve as the most senior hands-on individual contributor in its AI Engineering function within the centralized technology organization and AI & Automation organization. This role has no direct reports but carries technical authority, setting standards through architecture, code review, and mentoring. It also establishes enterprise-wide standards and governance for skills, plug-ins, and MCP connections, including work performed by other engineering teams.

The role builds on the Claude AI platform to create reusable skills and plug-ins, compose governed AI applications, establish retrieval over governed enterprise data, and turn experimental prototypes into tested, reliable, enterprise-ready applications. HUB currently uses Claude as its primary model and expects its technology stack to evolve toward agentic systems. Deep engineering work such as new backends, infrastructure, or complex integrations is executed by Enterprise Engineering to this role’s standards, then returned to the catalog for governance and publication. The position does not build or host foundational models and does not perform core machine learning or model training.

Compared with an AI Engineer, who builds and ships against established standards, the Senior AI Engineer establishes those standards, owns the technical decisions behind them, resolves complex problems, and is accountable for the reliability and governance of the function’s output. The role partners with business stakeholders, product, Enterprise Engineering, Data and Analytics, Cloud, Security, Privacy, and other teams to deliver governed AI capabilities, maintain the skill and plug-in marketplace and MCP catalog, and support released systems in production.

The position is based out of HUB’s Chicago office with a hybrid work arrangement. The expected salary range is $130,000 to $190,000, subject to factors including skills, experience, working location, business line, scope, and level.

Requirements

• At least 7 years of software or automation engineering experience, including at least 3 years building and shipping applications backed by large language models to production.
• Direct, recent, hands-on experience building and publishing Claude skills or plug-ins; broad large-language-model or framework experience without shipped skills and plug-ins is not sufficient.
• Demonstrated technical leadership as an individual contributor, including setting standards followed by other engineers, reviewing architecture and code, and mentoring without managing.
• Strong Python, REST API, and enterprise integration skills, with sound fundamentals in testing, version control, and monitoring.
• Hands-on experience with foundational models, including system and prompt design, skill and tool building, and function and tool calling.
• Experience with retrieval-augmented generation, embeddings, and vector stores, including chunking and reranking.
• Experience evaluating and monitoring systems backed by large language models, with practical understanding of cost, latency, and reliability tradeoffs.
• Experience operating in a regulated enterprise with security, governance, and access control integrated into normal delivery.
• Cloud experience with Azure or GCP / Vertex AI.
• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related technical field, or equivalent practical experience.
• Genuine software engineering depth rather than prompt-only development.
• Ability to influence engineers who do not report to the role, including engineers on other teams.
• Systems thinking and ability to design for consistency, resilience, and enterprise scale.
• Willingness to handle documentation, evaluation harnesses, access reviews, and production support.
• Coaching ability with evidence of raising the capability of other engineers.
• Clear technical communication with engineers, business stakeholders, and executive audiences.
• Accountability and ownership for quality, stability, governance, and delivery.
• Curiosity and adaptability as the AI stack evolves toward agents.

Nice To Haves

• Agent development and orchestration experience with LangGraph, CrewAI, or Claude Agent SDK.
• Model Context Protocol design, MCP server governance, and agent-to-agent patterns.
• Knowledge of RBAC, non-human or agent identity, and least privilege.
• 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.
• Experience as the senior technical voice in a new or maturing capability, including establishing standards where none existed.
• UiPath or Microsoft Power Platform exposure.
• Insurance or financial services industry experience and familiarity with audit and control expectations in a pre-IPO or public company environment.
• Familiarity with Git, CI/CD pipelines, modern software engineering practices, and tools such as Jira or Azure DevOps.

Responsibilities

• Build reusable skills, package them as plug-ins, and compose them into governed AI applications used across HUB business lines.
• Configure and tune foundational models for HUB use cases, including system and prompt design.
• Build retrieval-augmented generation, embeddings, vector-store, and multi-step workflow implementations over governed enterprise data.
• Productionize business-built AI prototypes into reliable, governed applications.
• Own engineering decisions concerning cost, latency, and reliability tradeoffs across the AI estate.
• Define and document engineering standards covering architecture patterns, testing, logging, documentation, and release discipline.
• Review architecture and code across the team and improve the quality of shipped work.
• Mentor AI Engineers and contract engineers and deliberately transfer knowledge.
• Set and uphold enterprise standards and governance for skills, plug-ins, and MCP across HUB, including work performed by other engineering teams.
• Partner with Enterprise Engineering on deep builds and define standards those builds must meet before returning to the catalog.
• Own the technical operation of the skill and plug-in marketplace and MCP catalog, including intake, publishing, versioning, maintenance, and deprecation.
• Apply access control, least privilege, and auditing to AI assets in partnership with Security, Privacy, and Cloud on identity and credentials.
• Ensure each AI asset published to the enterprise has a defined owner, documented behavior, and a support path.
• Establish and own evaluation harnesses, golden-set testing, guardrails, monitoring, and logging for consistent and reliable AI output at enterprise scale.
• Establish acceptance criteria and regression gating to prevent changes from silently breaking other cases.
• Provide production support for released skills, plug-ins, and applications, including incident response for non-deterministic systems.
• Translate governance, security, privacy, and regulatory requirements into engineering controls and audit-ready evidence.
• Partner with business stakeholders and the product function to turn prototypes into production-ready, governed capabilities.
• Partner with Enterprise Engineering, Data and Analytics, Cloud, and Security to deliver reliably and route deep builds appropriately.
• Represent AI Engineering in technical and governance forums.
• Participate in Agile ceremonies and document skills, applications, and technical decisions for handoff, audit, and maintenance.

Benefits

• Competitive base salary plus performance-based bonus; eligible annual bonuses, equity, and commissions may also be available for some positions.
• Comprehensive medical, dental, and vision coverage.
• 401(k) with company match.
• Paid time off and company holidays, including vacation, sick, personal, and floating holidays.
• Professional development and certification reimbursement.
• Structured training, licensing support, and ongoing development opportunities.
• Paid parental leave.
• Wellbeing program.
• Company-paid life and disability plans.
• Flexible spending account (FSA).
• Hybrid work arrangement based out of the Chicago office.
• Opportunity to set technical direction for HUB’s enterprise AI engineering function and asset platform.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior