WHAT WE DO

Site Reliability Engineering at Goldman Sachs sits at the intersection of software engineering, systems design, and production excellence. In this VP role, you will help engineer highly reliable, observable, and resilient platforms that support critical business services at scale. You will collaborate with multiple engineering teams to continually improve our production system architecture, facilitate fast delivery of new services, and reduce downtime.

This role is for software engineers who enjoy solving complex distributed system problems, building tools and platforms that make teams more effective, and championing SRE principles (such as SLOs, error budgets, and blameless post-mortems) across a large engineering organization.

KEY RESPONSIBILITIES

• Partner with engineering leadership to establish service level objectives (SLOs), service level indicators (SLIs), and error budgets.
• 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.
• Reduce operational toil by building automation, tooling, and self-service capabilities that remove repetitive manual work.
• Improve production readiness through load testing, performance tuning, capacity forecasting, chaos engineering and reliability reviews.
• Lead the response to complex, multi-system production incidents. Facilitate blameless post-mortems to identify root causes and drive long-term preventative actions.
• Promote sustainable operations by helping design healthy on-call models, clear escalation paths, and balanced pager responsibilities.

WHAT WE ARE LOOKING FOR

CORE TECHNICAL SKILLS

• Strong proficiency in at least one major programming language (e.g., Java, Python, or Node.js) with a focus on writing clean, maintainable code for tooling and automation.
• Hands-on experience with Infrastructure as Code (IaC) frameworks such as Terraform, Ansible, or CloudFormation.
• Deep understanding of containerization and orchestration technologies, specifically Docker and Kubernetes (K8s), including service meshes and ingress controllers.
• Advanced experience with major cloud providers (AWS, GCP, or Azure), specifically building and operating highly resilient cloud-native architectures.
• Proficiency with Observability stacks, including distributed tracing, logging, and metrics (e.g., Prometheus, Grafana, Splunk, Datadog, OpenTelemetry, ELK, or CloudWatch)
• 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(VPC), load balancing strategies in a distributed systems environment, database query performance tuning and identify cause for lagging