Staff Site Reliability Engineer
Zefr
About the role
About
Zefr is the leading global technology company enabling responsible marketing in walled garden social environments. Zefr’s solutions empower brands to manage their content adjacency on scaled platforms such as YouTube, Meta, TikTok, and Snap, in accordance with industry standard frameworks. Through its patented AI technology, Zefr offers brands and agencies more accurate and transparent solutions for social walled gardens. The company is headquartered in Los Angeles, California, with additional locations across the globe.
Responsibilities
- Support and build systems and tools that enable other engineers to generate, deploy, and manage product features and models both quickly and safely.
- Deploy and support a multi‑cloud, micro‑service architecture, including infrastructure tailored for ML workloads, deployed via Github Actions, ArgoCD & Kubernetes.
- Collaborate with other engineers, particularly the Machine Learning team, to architect secure, resilient, scalable, and cost‑efficient applications and ML systems/pipelines in AWS and GCP.
- Foster and push our DevOps culture and philosophy by encouraging continuous improvement across all engineering teams.
- Proactively maintain the health of production environments, including monitoring application performance and resource utilization.
- Participate in 24/7 on‑call rotation, respond to system performance issues and outages.
- Debug code at the application and infrastructure level.
- Mature our CI/CD workflows and release process.
- Maintain a forward‑thinking approach, actively researching and proposing new solutions.
- Propose and review Engineering Request for Comments (RFC) to drive Engineering architecture and practices.
Technology Stack
Core Infrastructure & Cloud Platforms
- Cloud Providers: Google Cloud Platform (primary), Amazon Web Services
- Infrastructure as Code (IaC): Terraform, Terragrunt
- Containerization & Orchestration: Docker, Kubernetes (experience with GKE and/or EKS expected), Helm, Kustomize
- Service Mesh: Istio
CI/CD & Automation
- CI/CD Pipelines: GitHub Actions
- GitOps / Continuous Delivery: Argo CD
- Primary Scripting/Automation Language: Python
Observability & Monitoring
- Monitoring & Alerting: Prometheus, Chronosphere, PagerDuty
- Telemetry Standards: OpenTelemetry
Application & Data Ecosystem (Supporting)
- Application Languages/Frameworks: Python, FastAPI, Flask, Node.js, React
- Data Streaming: Apache Kafka
- Data Processing/Transformation: Pandas, DBT
- Workflow Orchestration: Apache Airflow, Ray
Data Stores & Databases
- Relational Databases: PostgreSQL (including managed versions like AWS Aurora, GCP Cloud SQL)
- NoSQL Databases: DynamoDB
- Search Databases: OpenSearch
- Vector Databases: Qdrant
- Caching: Redis
- Data Warehousing: Snowflake
Requirements
- 7+ year job history designing, managing, deploying, and supporting Cloud Infrastructure in a production environment using major public cloud providers (GCP experience a huge bonus)
- Knowledge of GitOps including an understanding of modern CI/CD pipelines, techniques and technologies (Github Actions, GitLab, CircleCI, Argo CD, Flux)
- Proficiency with IaC and configuration management tools (Terraform, Terragrunt, OpenTofu, Crossplane, Pulumi)
- Production experience architecting, managing, deploying, and supporting container‑based workloads into Kubernetes clusters
- Strong problem‑solving experience, focusing on automation
- Proven track record of building and scaling reliability practices, including SLO/SLI frameworks, incident management, and capacity planning
- Heavy production experience with observability platforms and practices (Prometheus, Grafana, Chronosphere, Datadog, OpenTelemetry); ability to design monitoring strategies for complex distributed systems
- Knowledge of cloud networking (Mesh, NAT, Load Balancers, API Gateways, proxies, etc), cloud security, and cost optimization strategies
- Strong written and verbal communication, organization, and documentation skills
Benefits (US‑based employees)
- Flexible PTO
- Medical, dental, and vision insurance with FSA options
- Company‑paid life insurance
- Paid parental leave
- 401(k) with company match
- Professional development opportunities
- 10+ paid holidays off
- Summer Fridays (we leave early)
- In‑office, hybrid, and fully‑remote work options available
- In‑office lunches and lots of free food
- Optional in‑person and virtual events (we like to celebrate!)
Compensation (US‑based employees)
The anticipated salary for this position is between $190,000 and $210,000. Within the range, individual pay is determined by factors such as job‑related skills, experience, and relevant education or training. If your compensation expectations fall outside of this range, it may still be worth having a conversation.
Equal Opportunity
Zefr is an equal opportunity employer that embraces diversity and inclusion in the workplace. We are committed to building a team that represents a variety of backgrounds, skills, and perspectives because we know this only makes us better. We strongly encourage women, persons of color, LGBTQIA+ individuals, persons with disabilities, members of ethnic minorities, foreign‑born residents, and veterans to apply even if you do not meet 100% of the qualifications.
Requirements
- 7+ year job history designing, managing, deploying, and supporting Cloud Infrastructure in a production environment using major public cloud providers (GCP experience a huge bonus)
- Knowledge of GitOps including an understanding of modern CI/CD pipelines, techniques and technologies (Github Actions, GitLab, CircleCI, Argo CD, Flux)
- Proficiency with IaC and configuration management tools (Terraform, Terragrunt, OpenTofu, Crossplane, Pulumi)
- Production experience architecting, managing, deploying, and supporting container based workloads into Kubernetes clusters
- Strong problem-solving experience, focusing on automation
- Proven track record of building and scaling reliability practices, including SLO/SLI frameworks, incident management, and capacity planning.
- Heavy Production experience with observability platforms and practices (Prometheus, Grafana, Chronosphere, Datadog, OpenTelemetry); ability to design monitoring strategies for complex distributed systems.
- Knowledge of cloud networking (Mesh, NAT, Load Balancers, API Gateways, proxies, etc), cloud security, and cost optimization strategies.
- Strong written and verbal communication, organization, and documentation skills
Responsibilities
- Support and build systems and tools that enable other engineers to generate, deploy, and manage product features and models both quickly and safely.
- Deploy and support a multi-cloud, micro-service architecture, including infrastructure tailored for ML workloads, deployed via Github Actions, ArgoCD & Kubernetes.
- Collaborate with other engineers, particularly the Machine Learning team, to architect secure, resilient, scalable, and cost-efficient applications and ML systems/pipelines in AWS and GCP.
- Foster and push our DevOps culture and philosophy by encouraging continuous improvement across all engineering teams.
- Proactively maintain the health of production environments, including monitoring application performance and resource utilization.
- Participate in 24/7 on-call rotation, respond to system performance issues and outages.
- Debug code at the application and infrastructure level.
- Mature our CI/CD workflows and release process.
- Maintains a forward-thinking approach, actively researching and proposing new solutions.
- Propose and review Engineering Request for Comments (RFC) to drive Engineering architecture and practices.
Benefits
Skills
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