Senior Architect AI Engineering and Platforms

TransUnion

Confirmed live 2 days ago High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Chicago, ILReston, VA
Salary: $142,500–$237,500 / yr
Employment: Full-time
Posted: 5 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $190k

This role $190k

$131k $249k

below market most similar roles pay here above market

This role pays less than 52% of similar roles. Most pay $151,000–$228,950 — the blue band above. At the midpoint, this role pays about $190k versus about $190k for comparable roles.

Based on 240 similar postings.

Employer

About TransUnion

TransUnion is a global information and insights company and one of the "Big Three" credit reporting agencies, alongside Equifax and Experian.

TransUnion currently has 10 open roles on FindRole.

Listed pay typically runs $112,500–$187,500 across 9 roles with salary data.

Most-posted roles

View all roles at TransUnion

At a glance

TL;DR · Senior Architect AI Engineering and Platforms

Role Posting Log in to save

The Senior Architect AI Engineering and Platforms joins the AI Engineering and Platforms team to design, build, and operate foundational AI capabilities across multi-cloud and hybrid environments. This highly technical individual contributor will lead the architecture and delivery of scalable platform components, including agentic AI capabilities, observability, and operational guardrails. Key responsibilities involve translating business requirements into technical designs, mentoring engineers, and advancing DevOps practices for continuous integration and deployment. The role requires expertise in AWS, Azure, or GCP, alongside proficiency in Docker, Kubernetes, Terraform, and API design. Candidates must possess hands-on experience with Generative AI technologies such as vector search, Retrieval-Augmented Generation, and model fine-tuning. Additionally, the position utilizes distributed computing tools like Apache Spark and observability stacks including Prometheus, Grafana, and ELK.

Skills

GenAI AWS Azure GCP Kubernetes Docker Terraform AWS CloudFormation RAG Apache Spark Apache Hadoop Prometheus Grafana ELK) Stack Microservices Vector Search Knowledge Graphs Model Fine-tuning API Design

What you'll do

Design and implement scalable AI capabilities across multi-cloud and hybrid environments.
Lead the architecture and delivery of core AI platform components and capabilities.
Develop standardized development paths for agentic AI, observability, and operational guardrails.
Ensure the availability, performance, scalability, and security of all platform components.
Translate business and technical requirements into detailed platform designs and delivery plans.
Evaluate and integrate emerging technologies to enhance platform capabilities and user outcomes.
Apply best practices for data governance, metadata management, and security compliance.
Provide technical guidance, conduct design reviews, and mentor engineering team members.

What we're looking for

Bachelor’s or master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
10+ years of experience in ML engineering, data engineering, distributed systems, or platform development.
Hands-on experience building GenAI platforms or capabilities.
Experience delivering production GenAI solutions including retrieval quality, latency management, cost optimization, and evaluation-driven improvements.
Advanced expertise in at least one major cloud platform (AWS, Azure, or GCP) with knowledge of multi-cloud and hybrid architectures.
Proficiency with Docker, Kubernetes, infrastructure-as-code, API design, microservices, CI/CD, and distributed computing tools like Spark or Hadoop.
Hands-on knowledge of GenAI architecture including vector search, RAG, agentic frameworks, model fine-tuning, and observability tools like Prometheus or ELK.
Experience establishing standardized development patterns or "golden paths" for AI-enabled products (preferred).

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