Principal Software Architect - Observability & Data Platforms

ServiceNow•Orlando, FL

56d

About The Position

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.

Requirements

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 experience in software engineering, with a track record of delivering high-quality products 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.
Proficiency in Python, Java, or similar object-oriented languages.
Experience with modern front-end frameworks such as Angular, React, or Vue.
Strong knowledge of data structures, algorithms, object-oriented design, design patterns, and performance optimization
Familiarity with automated testing frameworks (e.g., JUnit, Selenium, TestNG) and integrating tests into CI/CD pipelines
Understanding software quality principles including reliability, observability, and production readiness.
Ability to troubleshoot complex systems and optimize performance across the stack.
Experience with AI-powered tools or workflows, including validation of datasets, model predictions, and inference consistency.
Comfort with development tools such as IDEs, debuggers, profilers, source control, and Unix-based systems

Nice To Haves

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.

Responsibilities

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.
Design and develop scalable, maintainable, and reusable software components with a strong emphasis on performance and reliability.
Collaborate with product managers to translate requirements into well-architected solutions, owning features from design through delivery
Build intuitive and extensible user experiences using modern UI frameworks, ensuring flexibility for customer-specific needs.
Contribute to the design and implementation of new products and features while enhancing existing product capabilities.
Integrate automated testing into development workflows to ensure consistent quality across releases.
Participate in design and code reviews ensuring best practices in performance, maintainability, and testability.
Develop comprehensive test strategies covering functional, regression, integration and performance aspects
Foster a culture of continuous learning and improvement by sharing best practices in engineering and quality
Promote a culture of engineering craftsmanship, knowledge-sharing, and thoughtful quality practices across the team.
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.
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.
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.
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.

Benefits

Build and deliver high-impact software that powers digital experiences for millions of users.
Collaborate in a culture that values craftsmanship, quality, and innovation.
Work symbiotically with AI and automation tools that enhance engineering excellence and drive product reliability.
Be part of a culture that encourages innovation, continuous learning, and shared success.

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