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# Site Reliability Engineer

- **Company:** Quantitative Systems
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $250,000 - $300,000
- **Contract:** Permanent contract
- **Skills:** Build Automation, Linux, Distributed Systems, Fault Tolerance, Python (Programming Language), Reliability Engineering, Prometheus, Real Time Systems, Grafana, Software Coding
- **Published:** November 8, 2026
- **Apply:** https://www.juju.com/job/28_25304_b7367c1a98bf77b9882e72e72ea35476

## About the Role

* 5+ years in an SRE, infrastructure, or production engineering role at a high-scale company.
 * Led the reliability efforts for mission-critical systems, preferably in a zero-downtime or low-latency environment.
 * Deep expertise in Linux systems, distributed architectures, and modern monitoring stacks (Prometheus, Grafana, etc.).
 * Strong coding skills in Python, Go, or similar enough to build the platform, not just configure it.
 * Experience with incident response at scale, blameless postmortems, and infrastructure as code.
 * Bonus: Familiarity with trading platforms, market data pipelines, or real-time processing systems.

## Description

This isn't a support role. It's an engineering position where uptime, performance, and automation drive revenue, where systems stability is the product. If you're an SRE who's spent time scaling internal platforms, eliminating toil, and tuning distributed systems at a place like Google, this is your next high-leverage move.

Why This Role

You'll own the reliability of trading infrastructure that processes high-volume, low-latency data across global markets. The systems are real-time, business-critical, and unforgiving. But that's exactly why the right engineer can make a massive impact.

This is a hands-on, systems-deep role. Think SRE meets production engineering, with traders instead of PMs, and decisions that directly affect capital in motion.

What You'll Do

 * Architect and harden distributed systems powering global trading operations.
 * Build automation to replace every manual task and remove human bottlenecks from production workflows.
 * Deploy real observability and alerting no noise, just signal.
 * Lead incident response, postmortem culture, and root-cause engineering.
 * Design fault-tolerant systems that self-heal and scale without a ticket queue behind them.
 * Partner with engineering and trading to align reliability work with business priorities.