Site Reliability Engineer

Requirements: 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. Experience tuning and validating timeseries anomaly detection models in a production observability context — this is a Required qualification, not a preferred one; anomalybased detection is a core function of this role.

Our client, an IT Services and Consulting company, is looking for a Site Reliability Engineer for their Woonsocket, RI/ Hybrid location.
 
Responsibilities:

• Own and drive the endtoend reliability, availability, and performance of critical retail and pharmacy technology platforms across hybrid cloud and onpremises environments.
• Establish and maintain SLI/SLO health, alerting strategies, observability standards, and businessaligned monitoring for the assigned application domain.
• Lead production incident response as Incident Commander, drive root cause analysis, postmortems, and continuous reliability improvements.
• Partner with engineering, product, and operations teams to embed reliability, resiliency, scalability, and operational readiness into system design and delivery.
• Build and optimize automation, selfservice capabilities, and operational tooling to eliminate toil, improve efficiency, and reduce manual intervention.
• Design and execute proactive reliability initiatives, including production readiness reviews, dependency risk assessments, fault injection, and chaos engineering exercises.
• Mentor engineers, champion SRE best practices, and enable teams to independently detect, respond to, and learn from production issues with minimal SRE involvement. Influence organizational adoption of SLOdriven engineering, observability, incident management, and reliability practices through collaboration, credibility, and measurable outcomes.

 
Requirements:

• 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 oncall Incident Commander (IC) for P1 or P2 incidents — structured leadership updates, not just participant involvement.
• Experience tuning and validating timeseries anomaly detection models in a production observability context — this is a Required qualification, not a preferred one; anomalybased 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.
• Handson experience designing SLIs, SLOs, and managing error budgets for customerfacing or businesscritical services.
• Deep observability platform experience: Prometheus, Grafana, Open Telemetry, and at least two of the log aggregation solutions (Loki, Splunk, Elasticsearch).
• Fleetscale 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 (GCP) and Rancher K3s.
• Advanced Kubernetes operational experience: debugging, resource management, networking policies, and workload failure modes. Experience with AIassisted tooling and development.
• Experience diagnosing and resolving workflow orchestration issues, batch processing failures, scheduler performance problems, and building observability on data pipelines: Apache Airflow and Tidal.
• Experience owning Production Readiness Reviews or service launch gates.
• Strong proficiency in transforming largescale operational and telemetry data into actionable business insights using SQLbased analytics and reporting frameworks: Google BigQuery, PostgreSQL.
• Handson 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.
• Infrastructureascode proficiency at production scale: Terraform or Ansible.
• Years of Experience: 14.00 Years of Experience

 
Why Should You Apply?

• Health Benefits
• Referral Program
• Excellent growth and advancement opportunities