Staff Software Engineer, Data & AI Platform Architecture - job 2 of 2

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money.

We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments.

We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com.

We are looking for a Staff Software Engineer with a platform mindset to help shape the future of our enterprise-wide Data, Analytics, and AI/ML platform capabilities.

This role is not focused on building one-off ML models or applications. Instead, you’ll build the foundational capabilities — the architecture, infrastructure, and reusable services — that power data-driven and AI-enabled products across the organization.

You’ll work with cross-functional teams to design and implement scalable, secure, and cost-efficient platform components that support GenAI, ML Ops, and advanced analytics use cases. You'll also play a key role in driving the adoption of shared capabilities across business units and regions.

You will report to the Senior Director of Platform Engineering.

You'll have the opportunity to:

• Architect and build core platform components that support the entire data, analytics, and AI/ML lifecycle — including data processing, feature engineering, model training/serving, observability, and governance.
• Define solution architectures for internal platform capabilities and reference implementations for common AI/analytics use cases.
• Lead the build vs. buy evaluation for components such as MLOps frameworks, vector stores, orchestration layers, and AI development tools.
• Stay current with modern data and ML architectures, including lakehouses, LLM orchestration patterns, and multi-tenant model serving.
• Partner with engineering, data science, and product teams to enable enterprise-scale adoption of shared platform services.
• Guide platform integration with public cloud services (AWS preferred), CI/CD pipelines, and observability stacks.
• Drive internal adoption by influencing engineering teams across global and regional product lines.
• Mentor engineers on platform best practices, architecture decisions, and scalability patterns.

Your background:

• 8+ years of software engineering experience, with deep exposure to building platforms for data, analytics, or ML/AI workloads.
• Strong background in distributed systems, cloud-native architecture, and data-intensive platforms.
• Proficiency in Python, Java, or Scala.
• Experience with big data processing frameworks (e.g., Spark, Flink) and modern data architectures (e.g., Lakehouse, Delta Lake, Apache Iceberg).
• Experience with cloud platforms (AWS preferred), including Terraform, Helm, or other Infrastructure-as-Code tools.
• Solid knowledge of Docker, Kubernetes, and building production-grade CI/CD pipelines.
• Track record of architectural leadership, influencing technology adoption and driving platform reuse across teams.

Bonus:

• Experience building internal ML platforms, MLOps frameworks, or self-service data science environments.
• Exposure to LLM-based applications and GenAI tooling (e.g., LangChain, vector databases, prompt orchestration).
• Understanding of security, compliance, and governance requirements for ML/AI workloads.
• Familiarity with platform observability (logs, metrics, tracing) for distributed systems.

Benefits/Perks:

• Great compensation package and bonus plan.
• Core benefits, including medical, dental, vision, and matching 401K.
• Flexible work environment, ability to work remotely, hybrid, or in-office.
• Flexible time off, including volunteer time off, vacation, sick, and 12-paid holidays.

Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's people first approach is award-winning; World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ in 24 countries, and Glassdoor Best Places to Work 2024 to name a few. Check out Experian Life on social or our Careers Site to understand why.

Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

#LI-Remote

This is a remote position.