AI Observability Engineering Technical Leader

The application window is expected to close on: 12/30/2026

The Platform and Security team within Cisco's AI Software and Platform Group designs and operates the infrastructure that powers Cisco's AI powered offerings, including Cisco Cloud Control, AI Defense, and AI Canvas. Within this team, the Observability Engineering group provides the metrics, traces, and logs needed to keep these services observable and ensure the most important workflows are continuously monitored. You’ll partner across the AI Software and Platform group to set observability standards, deliver platform solutions, and raise the bar for what "great" looks like in production reliability.

You’ll help build an agentic observability outcome where health insights can be surfaced faster and more intelligently than traditional dashboards and alerts.

You will define the observability platform vision and execute it end-to-end by partnering with software teams to instrument services correctly and consistently. You will deliver 100% coverage of distributed tracing in collaboration with development teams, ensuring tracing is implemented optimally with the right balance rather than tracing "everything." You will own and evolve Open Telemetry enablement—including libraries, process documents, and design patterns that accelerate adoption in Go and Python applications.

You will drive observability best practices across logging standards and cardinality management, then operate the platform components (Splunk Platform/Splunk Observability, OTEL collectors, and telemetry pipelines) to keep them dependable  will advance an agentic observability outcome so agents can analyze observability health signals and deliver distilled, actionable information more rapidly than conventional monitoring.

• Bachelor’s degree in Computer Science, Engineering (or related field) +12 years working in a platform services or Dev Ops role, with specific ownership of observability, or Masters + 8 years of related experience, or PHD + 5 years of related experience 2+ years of experience in Splunk Cloud and Splunk Observability (or Signal Fx): experience using Splunk Cloud for logging and Splunk Observability for metrics and traces.
• Experience with distributed tracing concepts and implementation, including instrumentation approaches and strategies for managing scope and overhead.
• Experience coding in Python and/or Go, including building libraries, automation, or operational tooling that supports observability platforms.
• Experience with distributed systems infrastructure, including Kubernetes, Open Telemetry (OTEL) collectors, and infrastructure-as-code (e.g., Terraform), plus familiarity with Helm charts and modern SDLC practices (e.g., Git Hub workflows).

Experience driving large-scale (100+ microservices) distributed tracing initiatives across an organization. Experience using AI agents to continually refine observability outcomes (e.g., detecting issues, improving routing/alerts, recommending instrumentation changes). Understanding of LLM observability, including familiarity with major providers and patterns for measuring reliability, latency, and quality signals. Deep understanding of AWS services commonly used in telemetry pipelines and distributed architectures.

At Cisco, we're revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We've been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.…