Principal Software Architect – Observability & Data Platforms at ServiceNow

Orlando, Florida, United States -

Full Time

Start Date

Immediate

Expiry Date

07 Jan, 26

Salary

0.0

Posted On

09 Oct, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Observability, Data Platforms, AI Integration, Distributed Systems, Telemetry, Monitoring, Data Pipelines, Cloud-Native Infrastructure, Kubernetes, CI/CD, OpenTelemetry, Prometheus, Predictive Analytics, Software Engineering, Technical Leadership, Mentorship

Industry

Software Development

Description

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, Prometheus, and modern observability tools. Strong grasp of cloud-native infrastructure and the Kubernetes ecosystem. Familiarity with CI/CD systems and developer workflow tooling. Experience with AI and agentic AI — including how to leverage it both as a product feature (e.g., anomaly detection, predictive analytics) and as a productivity enhancer (e.g., AI copilots, automated documentation, CI/CD validation). Experience balancing deep technical design with cross-functional collaboration and influence. Nice to Have Experience with long-term telemetry storage (e.g., Trino, S3 data lakes). Hands-on experience with Cribl for data routing, enrichment, and telemetry pipeline management. Contributions to open-source observability or platform tooling. Familiarity with AI-driven observability or predictive alerting systems. Background working with platform or SRE teams in high-scale environments. GCS-23 Additional Information Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact [email protected] for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.

Responsibilities

The Principal Software Architect will design and implement AI-enabled observability and data platforms to enhance operational reliability across hybrid cloud environments. This role involves defining architecture, shaping technical strategy, and leading cross-team alignment on observability and AI integration.