Principal Software Engineer – AI and Health Analytics

Oracle

Quick summary

Work type: On-site
Location: Austin, TX
Salary: $99,600–$223,400 / yr
Posted: 32 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $195k

This role $162k

$83k most similar roles pay here $258k

This role pays less than 76% of similar roles. Most pay $162,687–$227,837 — the shaded band above. At the midpoint, this role pays about $162k versus about $195k 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 606 open roles on FindRole.

Listed pay typically runs $97,500–$209,500 across 466 roles with salary data.

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At a glance

TL;DR · Principal Software Engineer – AI and Health Analytics

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As a Principal Software Engineer in the AI and Health Analytics team, you will be an individual contributor with over six years of experience, focusing on building large language model (LLM) and agent-based solutions to address critical business challenges such as revenue leakage, readmissions, and automation. Your day-to-day responsibilities include owning end-to-end features from data ingestion through transformation to delivering actionable insights. You must have a strong background in SQL and proficiency in Java and Python, along with expertise in artificial intelligence. This role involves working on scalable solutions within the healthcare analytics domain, where you will tackle complex business problems using advanced AI techniques.

Skills

Python Java SQL AWS Kubernetes Docker CI/CD PostgreSQL Terraform Git GitHub Linux RESTful_APIs Swagger JSON YAML Jenkins Ansible Prometheus Grafana

What you'll do

Design and implement large language model (LLM) solutions for business applications.
Develop agent-based systems to address specific industry challenges like revenue leakage and readmissions.
Manage full lifecycle of features, from data ingestion to transformation and insight generation.
Ensure end-to-end ownership of AI-driven health analytics projects.
Apply strong SQL knowledge in data processing and analysis tasks.