CNA
Principal AI Engineer
Chicago, IL, USA · Principal
Sponsorship not specified$97k-$189kDetected 13 days ago
CI/CDNLPLLMsAgentic AIAI OrchestrationComplianceAccountingLeadershipCommunicationProblem SolvingMentoringUnderwriting
About the role
- You have a clear vision of where your career can go.
- And we have the leadership to help you get there.
- This position has a deep understanding of AI engineering platforms, large language model (LLM) tooling, and enterprise software delivery from an end-to-end perspective.
Responsibilities
- Leads the scaling of AI solutions within the Underwriting portfolio, ensuring AI capabilities developed in product pods are industrialized into reliable, reusable, enterprise-grade services that integrate seamlessly into underwriting and operations workflows.
- Partners closely with underwriting, operations, and product teams to translate domain-specific workflows into AI-enabled solutions - including submission intake, risk triage, data enrichment, pricing signals, and decision support - ensuring alignment to real-world underwriting processes and measurable business impact.
- Designs AI integration patterns across core underwriting and operations systems - including underwriting workbench platforms and document processing pipelines - ensuring solutions are performant, scalable, and embedded directly into decisioning workflows.
- Acts as a senior technical mentor, developing engineers across the organization in AI-native practices including agentic coding patterns, context engineering, prompt-to-code workflows, and AI-assisted testing.
- Builds durable, self-sustaining team capability without ongoing coaching dependency.
- Drives reusability and cross-business-unit scalability of AI solutions, designing capabilities that can be leveraged across underwriting segments while accounting for differences in data, workflows, and risk profiles.
- Researches, evaluates, and recommends AI engineering tools, frameworks, and infrastructure (e.g., eval platforms, agent orchestration systems, environment provisioning automation), supporting build-vs-buy decisions with a focus on long-term scalability and maintainability.
- Expert knowledge of AI-native engineering practices, including agentic system design, LLM integration, multi-agent orchestration, and context engineering.
- Deep understanding of enterprise software delivery, including CI/CD pipelines, automated quality gates, cloud-native architecture, and production-grade system design.
- Excellent analytical and problem-solving skills with the ability to evaluate build-vs-buy trade-offs and make sound architectural recommendations.
Requirements
- Bachelor's degree in Computer Science, Engineering, or a related field required; Master's degree preferred.
Compensation
- I n certain jurisdictions, CNA is legally required to include a reasonable estimate of the compensation for this role.
This listing is sourced directly from CNA's careers page and normalized into a canonical job model.