Staff Software Engineer, Large-Scale Observability Platform

Intuit

San Diego (CA)

On-site

USD 189,000 - 255,000

Full time

3 days ago
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Job summary

Intuit is seeking a Staff Software Engineer for the Core PDX Observability Engineering team to design and deliver a next-generation logging and observability platform at scale. You will own architecture across on-prem and cloud deployments (AWS/GCP) and lead high-availability pipelines while mentoring engineers.

You will work on edge/collection agents, data routing, and AI-assisted tooling, with dashboards and alerts to monitor pipeline health and cost.

Qualifications

  • 8-10+ years of software engineering experience with large-scale distributed systems, logging/data pipelines, or observability platforms.
  • Deep expertise in building and operating high-throughput data pipelines at multi-TB/PB daily scale.
  • Strong hands-on experience with Kubernetes, containerized workloads, and sidecar/daemonset architectures.

Responsibilities

  • Architect, build, and evolve the One Intuit Logging system end-to-end from log generation to ingestion, routing, and storage.
  • Own and drive pipeline and cost optimization initiatives across the logging stack.
  • Lead design and development of core logging components (FELS, S3 Log Writer, Kinesis/CloudWatch Log Writer, Log Router, etc.).
  • Build observability into the platform itself—Grafana dashboards, metrics, and alerting for health and cost.
  • Provide technical leadership and mentorship, setting engineering standards and design direction across the team.

Skills

Go/Java/Python
Kubernetes
Cloud platforms

Education

Bachelor's degree in Computer Science

Tools

AWS
GCP

Job description

Intuit is seeking a Staff Software Engineer for the Core PDX Observability Engineering team to design and deliver a next-generation logging and observability platform at scale. You will own architecture across on-prem and cloud deployments (AWS/GCP) and lead high-availability pipelines while mentoring engineers.

You will work on edge/collection agents, data routing, and AI-assisted tooling, with dashboards and alerts to monitor pipeline health and cost.

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