WHAT WE DO
Core Reliability Engineering at Goldman Sachs sits at the intersection of software engineering, systems design, and production excellence. In this Vice President role, you will help engineer highly reliable, observable, and resilient platforms that software platforms that power our critical global financial services at scale. You will collaborate with engineering teams across the firm to elevate our production system architecture, facilitate the rapid delivery of new services, and build proactive guardrails against downtime.
As we modernize our global technology ecosystem, you will champion a software-first approach to reliability. This includes designing frameworks for measuring system health (SLOs and error budgets) alongside cutting-edge AIOps (Artificial Intelligence for IT Operations) frameworks. This role is designed for software engineers who enjoy solving complex distributed system problems, building intelligent platforms that make teams more effective, and spearheading proactive, AI-assisted operational excellence across a large engineering organization.
Key Responsibilities
- Collaborate with product developers to architect highly available, fault-tolerant, and self-healing systems. Conduct architectural reviews and introduce patterns like circuit breakers, graceful degradation, and rate limiting.
- Deploy and optimize advanced telemetry pipelines that utilize AIOps models to integrate metrics, logs, and traces for automated anomaly detection, intelligent alert correlation, and noise reduction to ensure high-signal alerting.
Minimize manual intervention and operational friction by writing robust software automation, self-service infrastructure APIs, and predictive workflows.
Lead load testing, performance tuning, and AI-enabled capacity forecasting to ensure our systems scale seamlessly ahead of market-driven demand.
- Partner with engineering leadership to establish clear service level objectives (SLOs) and indicators (SLIs), turning production health data into actionable software development priorities.
Drive the response to complex, multi-system production events, leveraging LLM-assisted diagnostics and AI-native engineering agents to automate root cause analysis (RCA) and accelerate Mean Time to Resolution (MTTR).
Help design sustainable, balanced on-call and ownership models that foster a healthy, software-driven approach to production management.
- Strong proficiency in at least one major programming language (e.g., Java, Python, or Node.js) with a focus on writing clean, maintainable code.
Practical exposure to AIOps features, automated log analysis, intelligent triage, and applying machine learning models to system telemetry pattern recognition.
Advanced experience with major cloud providers (AWS, GCP, or Azure), specifically building and operating highly resilient cloud-native architectures.
- Proficiency with OpenTelemetry standards and modern metric, logging, and distributed tracing systems.
Experience with automated testing and SDLC concepts, developing applications in a Linux environment, and sound knowledge of algorithms, data structures and software design.
Knowledge of networking protocols and load balancing strategies in a distributed systems environment.
Ability to analyze complex, distributed systems holistically, leveraging both traditional analytical skills and AI-driven insights to predict how individual components will interact under load.
Strong interpersonal skills to collaborate with product developers, influence architectural roadmaps, and drive reliability initiatives without direct authority.
- Ability to translate complex technical issues and AI-generated insights into clear, actionable recommendations for both technical and business stakeholders.
Highly motivated, proactive and capable of multi-tasking under pressure in a fast-paced environment without compromising quality.
Commitment to a blameless engineering culture where failures are treated as opportunities to learn and design automated, systemic safeguards.
Bachelor’s degree in Computer Science, System Engineering, Data Science, or a related technical field that involves programming.
7 to 10 years of experience in Software Engineering, Platform/DevOps Engineering, or Systems Design
Hands-on experience with Infrastructure as Code (IaC) frameworks such as Terraform, Ansible, or CloudFormation.
Understanding of containerization and orchestration technologies, specifically Docker and Kubernetes (K8s), including service meshes and ingress controllers.
ABOUT GOLDMAN SACHS
The Goldman Sachs Group, Inc. is a leading global investment banking, securities and investment management firm that provides a wide range of financial services to a substantial and diversified client base that includes corporations, financial institutions, governments and individuals. Founded in 1869, the firm is headquartered in New York and maintains offices in all major financial centers around the world.
Salary Range
The expected base salary for this New York, NY, United States-based position is $130000-$250000. In addition, you may be eligible for a discretionary bonus if you are an active employee as of fiscal year-end.
Benefits
Goldman Sachs is committed to providing our people with valuable and competitive benefits and wellness offerings, as it is a core part of providing a strong overall employee experience. A summary of these offerings, which are generally available to active, non-temporary, full-time and part-time US employees who work at least 20 hours per week, can be found here.
Skills Required
- Strong proficiency in at least one major programming language, such as Java, Python, or Node.js
- Experience with Infrastructure as Code frameworks such as Terraform, Ansible, or CloudFormation
- Deep understanding of Docker and Kubernetes, including service meshes and ingress controllers
- Advanced experience with AWS, GCP, or Azure and resilient cloud-native architectures
- Proficiency with observability technologies for distributed tracing, logging, and metrics
- Experience with automated testing, SDLC concepts, Linux application development, algorithms, data structures, and software design
- Knowledge of networking protocols and load-balancing strategies in distributed systems
- Strong collaboration, communication, analytical, multitasking, and stakeholder-influence skills
- Bachelor's degree in Computer Science, Systems Engineering, or a related technical field involving programming
- 7 to 10 years of professional experience
Goldman Sachs Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Goldman Sachs and has not been reviewed or approved by Goldman Sachs.
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Healthcare Strength — Healthcare is described as offering multiple plan options with subsidized premiums and prescription coverage. Materials indicate there are no pre-existing condition limitations in the U.S. summary.
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Retirement Support — Retirement benefits are considered competitive, including employer 401(k) matching and access to financial education and planning resources. These features position long-term savings as a core component of the package.
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Parental & Family Support — Family-support programs include paid parenting leave, family-care leave, and resources such as childcare support and lactation rooms in some offices. These offerings signal emphasis on supporting caregivers alongside work.
Goldman Sachs Insights
What We Do
At Goldman Sachs, we believe progress is everyone’s business. That’s why we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, Goldman Sachs is a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices in all major financial centers around the world. More about our company can be found at www.goldmansachs.com
