Role Overview

Goldman Sachs has embarked on one of its most ambitious engineering programs: the Consolidated Trade Ledger (CTL), a ground-up reimagining of the front-to-back architecture that underpins every trade the firm executes. CTL is a flagship initiative jointly sponsored by Global Markets and Engineering leadership, and it sits at the very heart of the firm's core technology strategy. This new, cloud-native platform will deliver the capacity, extensibility, scalability, and innovation capabilities to power the next two decades of growth for Global Markets, while simultaneously driving significant operational efficiencies.

We are seeking a Site Reliability Engineer to help build, run and continuously improve this business-critical service. The role combines software engineering, systems engineering and production expertise to improve the reliability, scalability, observability, incident response and operational efficiency of the CTL platform. 

Required Skills / Experience

• Strong programming ability in one or more modern languages – Java or Go strongly preferred – with experience building maintainable automation beyond simple scripts.
• Good understanding of networking, messaging, distributed systems, data structures, algorithms and software design fundamentals.
• Hands-on experience with observability tooling, including metrics, logging, tracing and dashboarding platforms such as Prometheus, Grafana, ELK or OpenTelemetry.
• Proven ability to investigate production issues, identify root causes and deliver durable engineering fixes that improve system behaviour and reduce repeat incidents.
• Excellent written and verbal communication skills, with the ability to translate complex technical issues into clear updates for technical, business and senior stakeholders.

Preferred Qualifications / Skills / Experience 

• Bachelor’s degree in Computer Science, Engineering or a related technical field, or equivalent practical experience.
• Experience with public cloud platforms – GCP preferred – cloud-native architecture, Kubernetes, microservices or service mesh technologies.
• Familiarity with relational databases and/or data-intensive platforms
• Experience supporting mission-critical production systems, preferably in a financial services environment. 
• Experience implementing progressive delivery approaches such as canary releases, blue/green deployments, feature flags or chaos/game days.
• Experience developing AI-assisted operations capabilities, such as alert enrichment, anomaly detection, triage support or runbook automation.

Key SRE Competencies

• Reliability engineering: SLOs, SLIs, error budgets, incident reduction and service health.
• Production excellence: monitoring, alerting, observability, runbooks, handoffs and operational readiness.
• Engineering mindset: automation, coding, debugging, testing, scalable design and systems thinking.
• Incident leadership: calm execution, escalation discipline, clear communication and blameless learning.