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# Software Engineer, Backend - AI Platform

- **Company:** LGA AIRPORT RESTAURANTS, L.P.
- **Location:** Mountain View, CA, United States
- **Experience:** Expert
- **Salary:** $118,000.0 - $212,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Continuous Integration, Data Streaming, Large Language Models, Backend, Kubernetes
- **Published:** August 1, 2026
- **Apply:** https://www.dice.com/job-detail/133b8ef8-cc90-402e-b18e-6b67809cd609

## About the Role

* 5+ years backend; strong Java; Kubernetes and CI/CD.
 * You've led backend architecture design - service boundaries, data flows, high-QPS systems - ideally in large-scale recommendation, search, or ads systems, and lived with the consequences.
 * You've refactored live production systems without breaking them: incremental migration, shadow verification, safe rollout are second nature.
 * Rigorous about safety: you design for rollback and blast-radius control by default.
 * Bonus: LLM-agent / AIOps exposure.

The US base salary range for this full-time position is listed below. Pay may vary based on a number of factors including job-related skills, level, experience, geographic location and relevant education or training. At NewsBreak, we design our overall rewards package to attract top talents. Depending on the position, the role may also be eligible for discretionary bonus and options. Your recruiter can share more details during the hiring process.

## Description

NewsBreak runs production AI agents today - they diagnose live incidents, analyze metrics, and triage user feedback. We're now upgrading our backend architecture to be AI-native: systems designed so that agents, tooling, and engineers can all operate them safely. This is a hands-on engineering role - you'll modernize live, high-traffic services behind NewsBreak's recommendation serving at scale, with a dual mandate: roughly half your time advances the architecture, half ships business impact.
What you'll do

 * Lead the architecture upgrade of our backend services - untangle legacy boundaries, define clean interfaces, build in first-class observability - and land it incrementally on live, high-QPS systems.
 * Build the infrastructure that lets AI agents act safely in production.
 * Automate high-toil engineering workflows into reliable, self-serve systems.
 * Deliver backend capabilities for product initiatives (experiments, growth systems, serving changes) when the business needs them.
 * Own reliability for what you build: observability, safe rollback, and lessons that feed the team's knowledge base.


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