Senior AI Software Engineer

CNA Insurance•Chicago, IL

3d•$72,000 - $141,000

About The Position

This individual-contributor role is responsible for designing, building, and operationalizing AI-driven solutions that integrate with enterprise systems. It combines hands-on engineering, architecture, and governance to deliver scalable, secure, compliant AI solutions aligned with business objectives. The engineer works with architects, product owners, business teams, IT, and vendors to identify and scale valuable use cases, turn prototypes into reliable production applications, and automate repeatable business processes. The role may include additional duties as assigned. The position typically reports to a Director or above. A bachelor’s degree in computer science or a related discipline, or equivalent work experience, is required. The role typically requires at least seven years of systems analysis and application development experience, including three or more years building AI solutions. Applicable certifications are preferred. Insurance industry knowledge is also preferred. For jurisdictions listed in the posting, the annual national base pay range is $72,000 to $141,000. Salary decisions may depend on relevant work experience, skills, certifications, and location. CNA describes its benefits package as comprehensive and competitive, with support for employees’ and family members’ physical, financial, emotional, and social wellbeing; specific benefits are not enumerated in the posting. The posting notes that CNA uses AI-enabled technology during recruiting and provides a contact for requesting disability accommodations.

Requirements

Strong programming skills in Java, Python, and TypeScript, and experience with FastAPI and Spring Boot for APIs and services.
Experience using AI-enabled development tools such as GitHub Copilot, Claude Code, Cursor, and MCPs.
Experience with RAG pipeline architecture and development.
Experience designing agentic systems for multi-step automation, including single-agent and multi-agent systems, orchestration, state and memory patterns, tool integration, and safe autonomy controls such as permissions, approvals, and auditability.
Experience with Google Cloud Platform, including GKE, Cloud Storage, PostgreSQL, Pub/Sub, Secret Manager, BigQuery, and Vertex AI.
Advanced knowledge of designing and building integration platforms, APIs, and web services.
Experience with CI/CD automation using tools such as Docker, GKE, GitHub, and GitHub Actions.
Strong analytical, problem-solving, and communication skills.
Experience with SQL and NoSQL data stores, including modeling and query optimization.
Automated testing experience, including unit and integration testing.
Working knowledge of React and front-end fundamentals, including components, state, and API integration.
Strong understanding of SRE and observability fundamentals, including logs, metrics, and traces, and their use in diagnosing distributed system behavior.
In-depth knowledge of the system development life cycle and system and application development technology alternatives.
Experience working in high-performing Agile teams.
Excellent communication and interpersonal skills, including the ability to work effectively with peers, IT management and staff, and internal and external business partners and clients.
Bachelor’s degree in computer science or a related discipline, or equivalent work experience.
Typically, a minimum of seven years of systems analysis and application development experience, including three or more years building AI solutions.

Nice To Haves

Preferred insurance industry knowledge.
Applicable certifications preferred.

Responsibilities

Design and build enterprise AI applications using LLMs, prompt workflows, RAG, and agent-based patterns.
Evaluate model quality, latency, cost, safety, and business effectiveness.
Implement responsible AI controls, observability, and governance for production AI systems.
Partner with architects, product owners, and business teams to identify and scale high-value AI use cases.
Convert prototypes into production-ready, reliable applications.
Enable automation of repeatable business processes using AI.
Develop APIs and microservices to expose AI capabilities.
Integrate AI solutions with enterprise platforms, including claims, document systems, and data platforms.
Ensure scalability, resiliency, and cost optimization.
Implement test automation, including unit, integration, and end-to-end testing.
Apply secure coding practices, including OAuth, JWT, and secrets management.
Mentor engineers and guide AI best practices.
Collaborate with business units, IT, and vendors.
Evaluate emerging AI technologies and recommend solutions.
Perform additional duties as assigned.