System Architect Director AI Platform Engineering
Job Location:
Chicago, IL - USA
Yearly Salary:
Posted on:
Vacancies:
Job Summary
You have a clear vision of where your career can go. And we have the leadership to help you get there.At CNA we strive to create a culture in which people know they matter and are part of something important ensuring the abilities of all employees are used to their fullest potential.
The System Architect (SA) Director for AI Platforms Engineering serves as the technical owner for the enterprise AI platform which is the shared foundation powering all AI and GenAI products across the organization. This leader owns the platforms architecture engineering standards and delivery roadmap translating strategic AI capabilities into reliable scalable and governed platform capabilities that accelerate every product team building on top of them.Working in close partnership with Enterprise Architects Product Management and Release Train Engineers (RTEs) the SA Director ensures that platform investments are tightly aligned to business outcomes compliance requirements and engineering excellence. This role combines the strategic depth of a principal architect with the hands-on leadership of a delivery-focused engineering director.
JOB DESCRIPTION:
Essential Duties & Responsibilities
Performs a combination of duties in accordance with departmental guidelines:
Own and continuously evolve the enterprise AI Platform reference architecture encompassing all critical layers including model serving orchestration engines data and knowledge grounding pipelines observability infrastructure and ensuring the platform scales reliably to enterprise-grade workloads and usage patterns.
Define and enforce platform-wide standards reusable design patterns and golden-path templates that enable product and feature teams to build deploy andoperateAI solutions safely consistently and with significantly reduced time-to-production.
Drive end-to-end delivery of new platform capabilities frominitialtechnical discovery and architecture design through prototyping hardening and full production rolloutwhilemaintainingmeaningful hands-on involvement at critical technical milestones to ensure quality and coherence.
Architect and operationalize the core platform service catalog including LLM gateway and routing layers prompt lifecycle management agentic orchestration frameworks Retrieval-Augmented Generation (RAG) pipelines vector stores model registries and rigorous automated evaluation infrastructure.
Build andmaintainrobust CI/CD and AIOps pipelines specifically designed for AI systems incorporating automated evaluation gates model and data versioning controls staged deployment promotion and continuous cost and performance optimization guardrails.
Architect enterprise-grade multi-agent and single-agent workflow patterns for high-value business use cases establishing clear standards for orchestration design state and memory management tool and API integration and safe autonomycontrols including human-in-the-loop approvals permission scoping and comprehensive audit trails.
Design and implement knowledge grounding systems spanning hybrid retrieval strategies semantic reranking ontology-driven entity modeling and knowledge graph integration to measurably improve AI output accuracy traceability and readiness for regulatory audit.
Embed responsible AI and compliance-by-design principles into every layer of the platform covering data privacy protections enterprise secrets management granular access controls output leakage prevention and model risk governance practices aligned to enterprise and regulatory standards.
ActivelyshapePI Planning by authoring well-defined Enabler Epics and articulating architectural outcomes that anchor near-term delivery and long-horizon platform capability roadmaps while contributing expert WSJF input to balance platform investment against feature team needs risk reduction and time-to-impact.
Directly manage mentor and grow a high-performing team of platform engineers solution architects and technical specialists hiring hands-on builders coaching technical leadership skills and sustaining a healthy innovation pipeline that continuously advances the organizations AI platform maturity.
May perform additional duties as assigned.
Skills Knowledge & Abilities
Deep AI Platform and AIOps engineering expertise including hands-on experience designing deploying and operating shared AI platform capabilities such as model serving layers LLM gateway and proxy services prompt registries vector databases and automated evaluation harnesses at enterprise scale.
Proven agentic system design capability with hands-on experience architecting multi-agent and single-agent workflow systems using orchestration frameworks such as Lang Graph Google ADK including tool and function calling patterns state and memory persistence strategies and robust safe autonomy controls.
Applied GenAI depth spanning LLM solution architecture patterns model selection and routing strategies advanced prompt engineering techniques fine-tuning and RLHF tradeoffs and production-grade RAG and hybrid retrieval system design and optimization.
Strong cloud-native and distributed systems architecture skills with deep GCP expertise across Vertex AI Cloud Run GKE Pub/Sub and BigQuery and a solid command of API and service-based design event-driven architecture and high-availability and fault-tolerant system patterns.
Knowledge grounding and semantic layer proficiency including experience building canonical ontology and entity models designing vector search and hybrid retrieval pipelines integrating knowledge graphs implementing reranking strategies and establishing citation and traceability mechanisms that support compliance.
Solid AIOps and platform reliability engineering experience including CI/CD pipeline design for AI systems automated evaluation and quality gates model and dataset versioning production monitoring and observability reliability engineering practices and systematic cost-performance optimization.
Practical responsible AI and security expertise with demonstrated experience implementing enterprise AI governance frameworks model risk management programs PII and data privacy controls audit and event logging and compliance-by-design patterns suited to regulated industries.
Strong SDLC and hands-on engineering fundamentals including Python proficiency architectural and code review practices comprehensive testing strategies for AI systems technical debt management refactoring discipline and operational readiness standards.
Scaled Agile (SAFe) leadership experience including decomposing long-horizon strategy into actionable Enabler Epics shaping PI planning outcomes.
Exceptional leadership and communication skills with a demonstrated ability to influence senior stakeholders and cross-functional teams negotiate complex technology tradeoffs mentor and develop engineers at all levels and translate deep technical concepts into compelling narratives for non-technical business audiences.
Education & Experience
Bachelors degree in Computer Science Software Engineering Information Technology or equivalent required;Mastersdegree in AI Machine Learning Data Science or related discipline strongly preferred.
10 years in software engineering and technical delivery withdemonstratedownership of large-scale distributed enterprise systems across the full SDLC frominceptionthrough production operations.
5 years in system or solution architecture witha track recordof producing reference architectures design patterns technical standards and enterprise-scale platform guardrails.
5 years of directpeopleleadership including hiring performance management career development and building high-performing engineering and architecture teams.
5yearshands-on designing delivering and operating AI/ML or GenAI platform capabilities in production with measurable outcomes in quality reliability and developer adoption.
Strong Pythonproficiencyand deep practical GCP experience Vertex AI GCP Agent Builder and Gemini with the ability to engage credibly in hands-on technical work alongside the engineering team.
Prior experience in regulated industries (insurance financial services or healthcare)stronglypreferred given stringent governance auditability and model risk management requirements.
Consulting or enterprise delivery background is a plus bringing structured problem-solvingandstakeholder management
#LI-KJ1 #LI-HYBRID
In certain jurisdictions CNA is legally required to include a reasonable estimate of the compensation for this District of Columbia California Colorado Connecticut Illinois Maryland Massachusetts New York and Washington the national base pay range for this job level is $97000 to $189000 determinations are based on various factors including but not limited to relevant work experience skills certifications and location. CNA offers a comprehensive and competitive benefits package to help our employees and their family members achieve their physical financial emotional and social wellbeing goals. For a detailed look at CNAs benefits please visit.
CNAutilizesAI-enabled technology during the recruiting process. For more information please visitourcareers page.
CNA is committed to providing reasonable accommodations to qualified individuals with disabilities in the recruitment process. To request an accommodation please contact
Required Experience:
Director
About Company
CNA provides insurance solutions to more than 1 million businesses and professionals worldwide. With more than 100 years of industry experience, CNA has earned a reputation as one of the most trusted commercial insurance companies in the business. We’re a powerful legacy built on expe ... View more
