Senior Information Security Infrastructure Engineer - Security Architecture - InfoSecNew$46K–$183K

The opportunity

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the…

What you'll do

  • Security telemetry ingestion: build and maintain ingestion of security-relevant data into Elasticsearch (cloud provider audit logs, identity/SaaS activity, endpoint and asset data). This means integrating with third-party and cloud provider APIs to pull telemetry: auth, pagination, rate limits, and handling schema changes. Both Elastic integrations and one-off custom integrations.

  • Keep the Elastic Cloud on Kubernetes clusters healthy. Monitor and upgrade: them regularly. This involves updating versions and builds. Manage capacity and shards. Handle index lifecycle management (ILM). Enable cross-cluster search (CCS).

  • Use Terraform to manage cloud infrastructure and Elasticsearch resources.: This includes managing pipelines, index templates, and alerts. Utilize Kubernetes and Helm to deploy scheduled ingest jobs.

  • Use AI automation and tooling to reduce toil. This includes self-healing jobs: and health checks. It also involves alerting, internal CLIs, and AI or agent-assisted workflows for investigation and operations.

  • Data quality & reliability: Own the "is the security data actually flowing correctly?" question. Monitor backfills. Ensure that schemas and fields are consistent. Keep an eye on costs.

  • Ability to operate Elastic and Elasticsearch in production. This includes: managing ingest pipelines, index templates, mappings, and queries, while ensuring that clusters are healthy and upgraded. Experience with ECK or Elasticsearch on Kubernetes is strongly preferred.

What they're looking for

  • Proven track record of using AI to accelerate development, debug complex: systems, and accelerate operations, while still owning the final outcomes.
  • Kubernetes - deploying and operating workloads (scheduled jobs, Helm charts,: operators); troubleshooting pods/jobs in a cluster.
  • Terraform - managing cloud and Elasticsearch resources as code.
  • API integration: consuming REST APIs for data ingestion: authentication, pagination, rate limiting concurrency, and error handling.