Software Architect; AI

• Job Posting - Salary Range: $115,747 - $208,344
• Department:
  Technology
• Flexible Time Off: 20 Days
• Schedule:
  
  Full Time
• Shift: Day Shift
• Compensation: USD 115,747 - USD 208,344 - yearly

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.

The Financial Services Division (FSD) Engineering team is looking for a Staff Software Architect. You will be reporting to the Software Development Director.

• Architect and evolve our real-time API platform for scalability, low-latency, and high availability (4–5 9s uptime).
• Lead design and implementation of platform-wide projects, such as event-driven architecture, observability, service mesh integration, and rate-limiting strategies.
• Define roadmaps across API platforms with emphasis on scalability, maintainability, and rapid experimentation.
• Apply enterprise architecture principles and standards while balancing near-term delivery and long-term platform goals.
• Build for leverage by creating reusable frameworks, automation, and internal tooling to accelerate teams.
• Integrate AI into every layer of architecture to support thoughtful, agentic system design.

Platform and Technical Leadership

• Lead technical design across consumer products and internal platforms.
• Support agent-based automation and apply MCP to promote scalable AI workflows.
• Shape cohesive end-to-end architecture spanning APIs, services, and frontends.

Collaboration and Influence

• Bring complex projects from concept to production, influencing technical direction across multiple teams.
• Lead technical deep dives, reviews, and postmortems to improve engineering quality.
• Promote adoption of tools like Git Hub Copilot, Cursor, Claude, and LLM-integrated workflows.
• Advance system-level thinking and reusability through shared scaffolds and frameworks.

Innovation and Organizational Impact

• Lead the Exponential Engineer Initiative to grow AI-first engineering through reusable agents, automation, and internal platforms.
• Promote agent-based design, prompt abstraction, and developer enablement across teams.
• Evaluate and apply latest technologies, especially Generative AI, to improve engineering and results.

• 8+ years in software engineering.
• 5+ years in architecture or principal roles.
• Experience with at least one modern backend language (Java, Go, Python, Rust, or Node.js).
• You have experience integrating LLMs with APIs (e.g., OpenAI, Anthropic, or similar).
• Experience with AI agent design, LLM orchestration (such as MCP), and integration of AI tools into developer workflows.
• Proficiency or active use of Git Hub Copilot, Cursor, Claude, and prompt-based development tools.
• Experience in developer enablement, automation platforms, or engineering transformation projects.
• Experience with API gateways, load balancing, caching, and observability tools (Splunk, Dynatrace).
• Familiarity with event-driven architectures, message queues (Kafka) and stream processing frameworks.
• Expertise in microservices, GraphQL, API-first design, and AWS-native systems.
• Knowledge of distributed systems, cloud platforms (AWS/GCP/Azure), and modern backend stacks (e.g., Node.js, Java, Go, or Python).
• Familiarity with event-driven architectures, message queues (Kafka) and stream processing frameworks.
• Operational experience in monitoring, observability, and incident response.
• Experience building multi-agent systems at scale.
• Exposure to AI observability platforms (prompt tracing, token analytics).
• Experience with fine-tuning or model customization.
• Background in platform engineering or internal developer platforms.
• Experience scaling AI systems to high-volume production workloads.
• Experience defining AI evaluation benchmarks and KPIs.
• Experience defining AI governance, compliance, and responsible AI practices.

Our compensation reflects the cost of labor across several U.S. geographic…