Principal Software Architect – Observability & Data Platforms

Company Description

It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone.

Job Description

We’re looking for a Principal Software Architect to design and implement next-generation, AI-enabled observability and data platforms that power real-time insights and operational reliability across hybrid cloud environments.

This role reports to the Senior Director of Engineering and partners closely with Platform, Product, and SRE leadership to define the technical vision and implementation strategy for observability and data systems across the organization.

You’ll lead the architecture and design of telemetry, monitoring, and data platforms that form the backbone of our engineering ecosystem — enabling visibility, intelligence, and scalability across our services.

What you get to do in this role:

• Define and evolve the architecture and design of AI-enabled observability and data platforms across distributed systems.
• Shape the technical strategy and design principles for metrics, traces, logs, and events pipelines.
• Drive the application of AI and agentic AI to enhance observability capabilities — including intelligent alerting, predictive analytics, and automated insights.
• Partner with platform, SRE, and application teams to standardize instrumentation and telemetry frameworks.
• Establish SLAs, SLOs, and data contracts that connect observability to system and business outcomes.
• Lead architectural design sessions, technical reviews, and cross-team alignment on observability and AI integration.
• Author architecture documents, design proposals, and technical playbooks to guide engineering teams.
• Provide deep technical mentorship on distributed systems, observability design, and data architectures.
• Drive the adoption of OpenTelemetry, modern observability standards, and AI-assisted tooling across engineering teams.
• Oversee platform scalability, cost efficiency, and reliability from an architectural perspective.
• Collaborate with leadership to align platform and AI roadmaps with enterprise engineering strategy.

Platform Architecture & Strategy

• Define the architecture and roadmap for a multi-cloud, multi-tenant observability platform.
• Design for scale, performance, and reliability with cost-aware architecture choices.
• Ensure systems are cloud-native, container-aware, and optimized for Kubernetes and service mesh environments.

Monitoring, Instrumentation & Developer Enablement

• Define architectural standards for scalable telemetry systems for logs, metrics, traces, and events.
• Design frameworks and best practices for instrumentation, monitoring, and observability adoption.
• Ensure observability validation is embedded into CI/CD and developer workflows.

Data Platform Architecture

• Design data pipelines for hot/cold telemetry paths and long-term retention.
• Define governance, privacy, and access control frameworks for observability data.
• Enable analytics and reporting across telemetry and operational data.

Technical Leadership

• Own architectural direction and design standards across observability and data teams.
• Champion engineering excellence, automation, and quality at scale.
• Mentor engineers and serve as an internal thought leader for telemetry and AI-driven platform design.

Qualifications

To be successful in this role you have:

• Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry.
• 15 years of related experience with a Bachelor's degree; or 12 years and a Master's degree; or a PhD with 8 years experience; or equivalent experience.
• Proven experience architecting and designing observability/data platforms at scale.
• Strong software engineering foundation (e.g., Python, Go, or Java).
• Expertise in distributed systems and data pipeline technologies (Kafka, Flink, Spark, etc.).
• Deep knowledge of OpenTelemetry, Prom