ServiceNow is looking to design and implement next-generation, AI-enabled observability and data platforms that power real-time insights and operational reliability across hybrid cloud environments.
Requirements
- Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving.
- 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.
- 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).
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.
Other
- Reports to the Senior Director of Engineering and partners closely with Platform, Product, and SRE leadership.
- Provide deep technical mentorship on distributed systems, observability design, and data architectures.
- Collaborate with leadership to align platform and AI roadmaps with enterprise engineering strategy.
- Collaborate with product managers to translate requirements into well-architected solutions, owning features from design through delivery.
- Promote a culture of engineering craftsmanship, knowledge-sharing, and thoughtful quality practices across the team.
