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Staff Platform Architect, Data & AI (Remote)

Role overview

Qualifications

  • 10+ years of software engineering experience focusing on data platforms, analytics infrastructure, and AI/ML systems
  • Bachelor's Degree or higher in science, technology, engineering or related field
  • Experience with distributed computing, cloud-native infrastructure, and large-scale data workloads on public cloud
  • Hands-on experience with AI agent-based architectures

Responsibilities

  • Evolve existing batch, analytics, and MLOps platforms for reliability and efficiency
  • Develop infrastructure for semantic and ontology layers
  • Design agent-driven data access patterns and APIs for platform capabilities
  • Guide technology adoption across engineering teams and mentor engineers

About the company

BillFixers (acquired by Experian) logo

BillFixers (acquired by Experian)

Consumer Services

BillFixers negotiates on behalf of consumers to lower their bills without all the hassle of having to call customer service. Our team of expert negotiators will contact your service providers on your behalf and negotiate better deals at lower prices. We find promotional rates, customer loyalty discounts, special packages, and additional credits to get you the lowest bill possible.

Company details

IndustryConsumer Services
Company size11 - 50

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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

About the Role:

We are looking for a Staff Platform Architect to join our Data & AI Platform Architecture team. We are a small, high-use group that shapes technology strategy across analytics products, AI/ML enablement, and data infrastructure at enterprise scale.

This is a role for someone with deep fundamentals in data, analytics, and MLOps platforms. You should also know how to evolve them to serve both humans and AI agents, internal and external, with equal thoughtfulness.

You will extend and evolve a set of existing platforms including our MLOps infrastructure, batch platform, analytics stack, and managed analytics offerings, while leading greenfield design of our AI-ready data foundation. You will report to the Sr. Director of Platform Engineering

 

What you'll do here

  • Evolve our existing batch, analytics and MLOps platforms improving reliability, cost, and operational efficiency.
  • Develop the infrastructure for our semantic and ontology layers. (including authoring and governance tooling, lifecycle management, and catalog integration)
  • Design the usage infrastructure that makes these layers usable by any downstream consumer, including BI tools, ML pipelines, AI agents, internal users and client-facing products
  • Design agent-driven data access patterns, including permission-aware semantic discovery, identity federation for AI workloads, and APIs that expose platform capabilities to LLM-based agents.
  • Ensure shared platform capabilities translate cleanly into client-facing products.
  • Guide technology adoption across engineering teams by making the right architectural choices well-reasoned and easy to follow.
  • Lead focused prototyping and R&D efforts with analytics product and engineering teams to validate new AI and analytics capabilities before broader platform investment.
  • Mentor engineers across the organization in your areas of expertise, with a focus on first-principles thinking, system design, and product awareness.

Qualifications

  • 10+ years of software engineering experience, with a deep focus on data platforms, analytics infrastructure, and AI/ML systems at enterprise scale.
  • Bachelor's Degree or higher in science, technology, engineering or related field
  • Experience building or operating MLOps platforms from data access and feature engineering through model deployment and monitoring.
  • Experience with data modeling, metadata, lineage, and data governance
  • Hands-on experience with AI agent-based architectures, in the context of governed data access, semantic discovery, and retrieval over enterprise data assets.
  • Experience with distributed computing, cloud-native infrastructure, and the cost and operational dynamics of running large-scale data workloads on public cloud (AWS preferred).
  • Comfort with infrastructure as code and operating production workloads
  • Experience influencing architectural decisions at scale, across teams and departments
  • Experience building enterprise-scale data and MLOps platforms on Databricks
  • Experience designing federated catalog architectures that deliver governed, unified data access across existing platforms and data silos.
  • Experience with security, compliance and governance considerations for AI/ML workloads, including data residency, access control and audit requirements.
  • Background in credit risk, financial services, or other regulated data domains where governance and compliance constraints shape platform design.

Additional Information

Benefits/Perks:

  • Great compensation package and bonus plan
  • Core benefits including medical, dental, vision, and matching 401K
  • Flexible work environment, ability to work remote, hybrid or in-office
  • Flexible time off including volunteer time off, vacation, sick and 12-paid holidays
  • Explore all our exciting benefits here: https://yourexperianbenefits.com/cand-index.html
  • #LI-Remote

Our uniqueness is that we celebrate yours. Experian's people first, inclusive and purpose driven culture is multi award-winning; World's Best Workplaces™ 2025 (Fortune Global Top 25), Great Place To Work™ in 26 countries to name a few. Check out Experian Life on social or explore our Careers Site to understand why.

Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay range for this position is listed above. Within this range, individual pay is determined by work location and additional factors such as job-related skills, experience, and education. This position is also eligible for a variable pay opportunity and a comprehensive benefits package.

Recruitment Fraud Awareness - Experian's recruitment process is conducted only through authorised channels. Recruitment communications will only be sent from an @experian.com email address. Experian will never ask candidates to make any payment as part of an application, interview, assessment, onboarding, or recruitment process. To apply for roles or verify opportunities, please visit experian.com/careers.

Experian is proud to be an Equal Opportunity Employer for all groups protected under applicable federal, state and local law, including protected veterans and individuals with disabilities. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

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Marcus Rivera

Chief Revenue Officer

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linkedin.com/in/marcusrivera
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