Experian

Staff AI Architect, Remote

US$115,747-$208,344Posted 27 days ago

Job Description

Company Description

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more. Experian invests in people and new advanced technologies to unlock the power of data. We have an amazing team of 25,200 people in 32 countries.

Job Description

Overview

We are looking for a Staff AI Architect to lead the technical vision and architectural strategy for our cloud-native platform and agentic AI capabilities. You will shape how our systems are designed and evolved at scale. You will also promote infrastructure excellence across the organization, driving their design, deployment, and evolution at scale. You will report to the Sr. Principal Engineer. This is an individual contributor position.

Responsibilities

  • Manage and evolve the end-to-end architectural blueprint for cloud-native applications at scale — covering compute, data, networking, security, and observability layers on AWS.
  • Define and promote agentic AI architecture patterns, including multi-agent systems, tool orchestration, memory and retrieval strategies, LLM routing, guardrails, and feedback loops. Translate these patterns into relevant standards and reusable reference architectures.
  • Establish and govern DevOps standards across the organization: CI/CD pipeline design, GitOps practices, deployment strategies (blue/green, canary, progressive delivery), environment parity, and release engineering.
  • Design and oversee platform infrastructure. This includes ECS, Kubernetes clusters (EKS), service mesh, API gateway strategy, secrets management, IAM/RBAC governance, and data stores like DynamoDB, Aurora RDS, Postgres, Elastic/OpenSearch. Additionally, it involves multi-account/multi-region AWS topology.
  • Lead architecture reviews and provide binding technical decisions on high-risk c

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