Sr. Site Reliability Engineer

Job description

# Sr. Site Reliability Engineer > Tiger Analytics Inc. · Washington, United States · — · Posted 2026-05-08 **Workplace:** on_site **Department:** Data Engineering ## Description ### **Role Overview** We are seeking a high-caliber **Site Reliability Engineer (SRE)** to join our Forward Engineering team. You will be the guardian of our production ecosystems, ensuring that our complex, data-driven AI platforms remain resilient, scalable, and highly performant. This role is a hybrid of software engineering and systems architecture, with a specialized focus on **MLOps**—bridging the gap between model development and production-grade reliability. ### **Key Responsibilities** ### **1\. Reliability & Performance Engineering** - **SLA/SLO Management:** Define, monitor, and maintain Service Level Objectives (SLOs) and Service Level Indicators (SLIs) for critical AI/ML services. - **Error Budgeting:** Manage error budgets to balance the velocity of feature releases from the ML team with the stability of the production environment. - **Scalability:** Architect and manage auto-scaling strategies for **Kubernetes (GKE)** to handle fluctuating workloads during model training and high-volume inference. ### **2\. MLOps & AI Infrastructure** - **Model Serving Reliability:** Ensure the high availability of **Vertex AI endpoints** and custom inference services. - **GPU/TPU Optimization:** Monitor and optimize compute resource utilization (accelerators) to ensure cost-efficient performance for Large Language Models (LLMs). - **Pipeline Resilience:** Support and stabilize ML pipelines (Vertex AI Pipelines/Kubeflow) to ensure seamless data flow from ingestion to model retraining. ### **3\. Automation & Orchestration (Eliminating "Toil")** - **Infrastructure as Code (IaC):** Use **Terraform** or Pulumi to provision and manage consistent, version-controlled cloud environments. - **CI/CD & GitOps:** Design and optimize robust deployment pipelines for both application code and ML models using GitHub Actions, Cloud Build, or ArgoCD. - **Task Automation:** Develop custom Python or Go scripts to automate repetitive operational tasks, self-healing mechanisms, and resource cleanup. ### **4\. Monitoring, Alerting & Incident Response** - **Observability:** Build and manage comprehensive dashboards using **Prometheus, Grafana, or Google Cloud Operations Suite (Stackdriver)**. - **Incident Management:** Act as a primary responder in on-call rotations, leading the technical resolution of production outages. - **Blameless Post-Mortems:** Conduct deep-dive root cause analysis (RCA) to ensure systemic issues are identified and permanently remediated through code. ## Requirements **Orchestration:** Expert-level knowledge of **Kubernetes (K8s)** and Docker. **MLOps Stack:** Familiarity with tools such as **Kubeflow, Vertex AI, MLflow, or DVC**. **Scripting:** Strong proficiency in **Python** (for automation) and Bash; knowledge of Go is a plus. **Data Systems:** Experience managing the reliability of data-heavy services (BigQuery, Pub/Sub, or Vector Databases like Pinecone/Milvus). **Networking:** Solid understanding of VPCs, Load Balancers, DNS, and secure service mesh (Istio/Anthos). ## Benefits Benefits Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility. _**Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.**_ ## Apply [Apply at Tiger Analytics Inc.](https://apply.workable.com/tiger-analytics/j/AF0D1A3499/apply) --- Powered by [Workable](https://www.workable.com)