Senior Architect AI Engineering and Platforms

TransUnion•Chicago, IL

9d•$142,500 - $237,500•Hybrid

About The Position

The Senior Architect, AI Engineering and Platforms is a highly technical, hands-on individual contributor responsible for designing, building, and operating core AI platform components. The role contributes to the technical vision for foundational AI platforms and leads the architecture and delivery of assigned platform capabilities supporting internal and external users across multi-cloud and hybrid environments. The position partners with Product, Engineering, and other cross-functional teams to deliver scalable, secure, and reliable AI platforms and AI-enabled solutions. This is a hybrid position requiring regular work virtually and in person at an assigned TransUnion office for a minimum of two days per week. The role reports to the Director for Software Development.

Requirements

Bachelor’s or master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience supporting the design and delivery of complex AI, data, or platform solutions.
10 or more years of experience across machine learning engineering, data engineering, distributed systems, or platform development, including at least three years of hands-on experience building GenAI platforms or capabilities.
Hands-on experience delivering production GenAI solutions for internal or external users, including retrieval quality, latency management, cost optimization, and evaluation-driven quality improvements.
Experience building scalable AI or data platform components adopted by multiple teams, with measurable developer or user experience outcomes.
Strong problem-solving, analytical, communication, and collaboration skills, including the ability to explain complex technical concepts to technical and nontechnical audiences.
Advanced expertise in at least one major cloud platform (AWS, Microsoft Azure, or GCP), with working knowledge of multi-cloud and hybrid architectures.
Strong proficiency with Docker, Kubernetes, infrastructure as code, API design, microservices architecture, continuous integration, and continuous deployment.
Hands-on knowledge of GenAI architecture and engineering, including vector search, knowledge graphs, RAG, agentic frameworks, model fine-tuning, evaluation frameworks, and cost management.
Experience with distributed computing technologies such as Apache Spark or Apache Hadoop and infrastructure-as-code tools such as Terraform or AWS CloudFormation.
Experience implementing cloud security and compliance controls and using observability tools such as Prometheus, Grafana, and the ELK Stack.

Nice To Haves

Experience establishing standardized development patterns or “golden paths” for AI-enabled products.
Familiarity with metadata management, data governance, and data quality frameworks.
Experience optimizing AI platforms for retrieval quality, latency, reliability, and cost.
Experience evaluating and integrating emerging AI technologies into enterprise-scale platforms.
Experience providing technical mentorship and influencing engineering practices across multiple teams.

Responsibilities

Contribute to the technical vision for foundational AI platforms and lead the architecture and delivery of assigned platform capabilities.
Design and implement scalable AI capabilities across multi-cloud and hybrid environments.
Implement and evolve standardized development paths for AI-enabled products, including agentic AI capabilities, observability, evaluations and measurement, operational controls, and guardrails.
Ensure the availability, performance, scalability, and security of assigned platform components.
Partner with cross-functional teams to translate business and technical requirements into platform designs and delivery plans.
Evaluate, prototype, and integrate emerging technologies that enhance platform capabilities and user outcomes.
Apply best practices for data governance, metadata management, data quality, security, and compliance.
Provide technical guidance, conduct design reviews, and mentor engineers.
Advance automation and DevOps practices supporting continuous integration and deployment of data and AI services.

Benefits

Day-one eligibility for medical, dental, and vision coverage, plus supplemental plan options and eligible dependent coverage on select plans.
Health Savings Account (HSA) and Flexible Spending Account (FSA) options.
Company-paid basic life and AD&D insurance; optional voluntary life and AD&D insurance; short- and long-term disability coverage.
Optional legal plan, pet insurance, and travel accident coverage.
Adoption assistance, fertility planning coverage, caregiver support, Dependent Care FSA with possibility of employer match, and complimentary Care@Work membership.
Up to 12 weeks of paid parental leave with eligibility for a gradual return.
401(k) with employer match and Employee Stock Purchase Plan (ESPP).
Financial wellness resources and career coaching; optional long-term care insurance.
Tuition reimbursement.
Flexible time off for exempt employees or paid time off for nonexempt employees.
Up to 12 paid holidays per year.
Commuter benefits and employee discounts.
Charitable gift matching and paid volunteer time off, as well as corporate volunteer events.
24/7 access to professional therapy, coaching, emotional well-being programs, guided meditation, and resources supporting physical, mental, social, and financial wellness.
Regular full-time non-sales positions may be eligible for the annual bonus plan; certain positions may also be eligible for long-term incentives and other payments.