Staff Software Engineer, Data & AI Platform Architecture

Experian Group; United States; Remote; USD 90,000 - 160,000; Full time

Job summary

Join a forward-thinking company as a Staff Software Engineer and help shape the future of enterprise-wide Data, Analytics, and AI/ML platform capabilities. In this role, you will architect and build foundational components that support data-driven and AI-enabled products across the organization. Collaborate with cross-functional teams to design scalable, secure, and efficient platform components while driving the adoption of shared capabilities. This role offers a unique opportunity to influence technology adoption and mentor engineers on best practices in a flexible work environment that values innovation and diversity.

Benefits

Great compensation package and bonus plan

Medical, dental, vision benefits

Matching 401K

Flexible work environment

Flexible time off including volunteer time off

Qualifications

• 8+ years of software engineering experience focused on data and ML/AI platforms.
• Strong background in cloud-native architecture and distributed systems.

Responsibilities

• Architect and build core platform components for data and AI/ML lifecycle.
• Lead evaluations for MLOps frameworks and AI development tools.

Skills

Software Engineering

Distributed Systems

Cloud-native Architecture

Data-intensive Platforms

Python

Java

Scala

Big Data Processing (Spark, Flink)

CI/CD Pipelines

MLOps Frameworks

Tools

AWS

Terraform

Helm

Docker

Kubernetes

Job description

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:

1. 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.
2. Define solution architectures for internal platform capabilities and reference implementations for common AI/analytics use cases.
3. Lead the build vs. buy evaluation for components such as MLOps frameworks, vector stores, orchestration layers, and AI development tools.
4. Stay current with modern data and ML architectures, including lakehouses, LLM orchestration patterns, and multi-tenant model serving.
5. Partner with engineering, data science, and product teams to enable enterprise-scale adoption of shared platform services.
6. Guide platform integration with public cloud services (AWS preferred), CI/CD pipelines, and observability stacks.
7. Drive internal adoption by influencing engineering teams across global and regional product lines.
8. Mentor engineers on platform best practices, architecture decisions, and scalability patterns.

Your background:

1. 8+ years of software engineering experience, with deep exposure to building platforms for data, analytics, or ML/AI workloads.
2. Strong background in distributed systems, cloud-native architecture, and data-intensive platforms.
3. Proficiency in Python, Java, or Scala.
4. Experience with big data processing frameworks (e.g., Spark, Flink) and modern data architectures (e.g., Lakehouse, Delta Lake, Apache Iceberg).
5. Experience with cloud platforms (AWS preferred), including Terraform, Helm, or other Infrastructure-as-Code tools.
6. Solid knowledge of Docker, Kubernetes, and building production-grade CI/CD pipelines.
7. Track record of architectural leadership, influencing technology adoption and driving platform reuse across teams.

Bonus:

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

Benefits/Perks:

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

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.