Why This Role Stands Out
This hybrid SRE role offers a fantastic opportunity to leverage your extensive experience in distributed systems and observability to drive critical improvements in Ztek Consulting's production environment. You'll thrive here if you excel in incident command, possess strong Python, React, and Java skills, and have a deep understanding of cloud platforms and Kubernetes, all while enjoying the flexibility of a hybrid work model. Apply now to contribute to a leading technology company and advance your career in a challenging and rewarding position.
Quick Overview
Job Description
Role:- SRE
Remote - Woonsocket, RI hybrid
Job Description/ Responsibilities
8+ years of Senior Software engineering experience in SRE, DevOps, platform engineering, or related production-systems roles in distributed systems at production scale with active on-call responsibility
Demonstrated experience as an on-call Incident Commander (IC) for P1 or P2 incidents structured leadership updates, not just participant involvement
Experience tuning and validating time-series anomaly detection models in a production observability context this is a Required qualification, not a preferred one; anomaly-based detection is a core function of this role
Strong programming proficiency in Python, React, and Java at production quality capable of writing operational tooling that other engineers will rely on
Hands-on experience designing SLIs, SLOs, and managing error budgets for customer-facing or business-critical services
Deep observability platform experience: Prometheus, Grafana, OpenTelemetry, and at least two of the log aggregation solution (Loki, Splunk, Elasticsearch)
Fleet-scale deployment awareness: familiarity with progressive rollout strategies, blast radius management, and configuration drift as a reliability risk in large unattended node deployments
Strong cloud platform expertise in Google Cloud Platform (Google Cloud Platform) and Rancher K3s.
Advanced Kubernetes operational experience: debugging, resource management, networking policies, and workload failure modes. Experience with AI-assisted tooling and development.
Experience diagnosing and resolving workflow orchestration issues, batch processing failures, scheduler performance problems, and building observability on data pipeline : Apache Airflow and Tidal.
Preferred Qualifications
Experience owning Production Readiness Reviews or service launch gates.
Strong proficiency in transforming large-scale operational and telemetry data into actionable business insights using SQL-based analytics, and reporting frameworks: Google BigQuery, PostgreSQL.
Hands-on chaos or fault injection experience.
TIC (Technical Incident Commander) certification or equivalent structured incident command training
Experience operating distributed systems in retail, pharmacy, healthcare, or other operationally sensitive environments where failures have direct patient or customer impact
LLM integration for operational use cases (alert summarization, runbook suggestion, incident triage assistance) design or implementation experience
Experience with streaming data platforms: Kafka.
Experience with service mesh and traffic management: Istio, Envoy.
Infrastructure-as-code proficiency at production scale: Terraform or Ansible
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