AI Platform Reliability Engineer

Oracle

Quick summary

Work type: On-site
Location: Austin, TX
Salary: $79,200–$209,500 / yr
Posted: 12 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $203k

This role $144k

$59k most similar roles pay here $264k

This role pays less than 85% of similar roles. Most pay $162,000–$244,287 — the shaded band above. At the midpoint, this role pays about $144k versus about $203k for comparable roles.

Based on 240 similar postings.

Employer

About Oracle

Oracle Corporation is a leading multinational technology company specializing in database software, cloud computing, and enterprise software.

Oracle currently has 755 open roles on FindRole.

Listed pay typically runs $97,500–$209,500 across 568 roles with salary data.

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At a glance

TL;DR · AI Platform Reliability Engineer

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Oracle Health is hiring an AI Platform Reliability Engineer, a senior individual contributor role within the product development team, focusing on ensuring the reliability of its AI agent platform and analytics workflows. This engineer will build observability tools for monitoring and tracing AI systems, implement robust release management practices including rollback controls, and design evaluation strategies to detect performance issues in production. The ideal candidate has expertise in CI/CD, incident response, and operational tooling, with a strong background in reliability engineering and scripting or software development. This role is crucial for maintaining trust in AI outputs and ensuring that new capabilities can scale safely across Oracle Health’s enterprise platforms.

Skills

CI/CD Kubernetes Docker Terraform AWS Azure GCP Prometheus Grafana Python Java Go PostgreSQL Redis Git Jenkins Ansible Kafka Elasticsearch Kibana Selenium JUnit SonarQube Docker Swarm OpenShift

What you'll do

Build and maintain observability, logging, tracing, and monitoring for AI agents and workflows.
Implement release, rollout, rollback, and versioning controls for AI systems and configurations.
Design production evaluation practices to detect regressions, silent failures, and performance issues.
Support incident response, triage, root-cause analysis, and operational reporting for AI issues.
Contribute to data monitoring and reliability workflows, including detection of anomalies and schema drift.
Implement latency, throughput, and cost monitoring controls for AI-enabled systems.

What we're looking for

6+ years of experience in AI/ML platform operations, including CI/CD and release management.
Strong background in observability, logging, tracing, monitoring, and alerting for production systems.
Expertise in incident response, root cause analysis, and operational reporting for complex issues.
Experience with evaluation practices to detect regressions, silent failures, quality drift, and performance issues.
Proficient in scripting or software development, versioning, and configuration management.

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