Senior Site Reliability Engineer

Location: Poland only, fully remote

Job Type: B2B, full time

Application Reliability & Performance

• Ensure the availability, reliability, and performance of high-traffic Java-based applications in a distributed environment.
• Troubleshoot and resolve complex issues across production and non-production environments.
• Participate in pre- and post-deployment performance testing and monitoring to continuously improve application performance.
• Optimize Java application performance with a focus on JVM tuning, efficient resource utilization, and horizontal scaling.

Monitoring, Observability & AIOps

• Deploy and manage the Grafana stack (Grafana, Prometheus, Loki, Mimir, Alloy) to deliver real-time monitoring, logging, and alerting.
• Implement and refine observability strategies that enhance visibility into application and infrastructure health.
• Create and maintain dashboards, alerts, and log queries for comprehensive system health monitoring.
• Integrate AI/ML models into the observability pipeline for anomaly detection, predictive alerting, and intelligent alert correlation and noise reduction.

AI & Agentic Workflow Engineering

• Design, build, and operate agentic AI workflows that automate operational tasks such as alert triage, root cause analysis, runbook execution, and incident summarization.
• Develop tool-calling LLM agents that interact with infrastructure APIs (Kubernetes, Grafana, Jira, Slack, PagerDuty) to execute diagnostic and remediation actions autonomously or with human-in-the-loop approval.
• Build and maintain MCP (Model Context Protocol) servers and integrations that expose internal systems as tool surfaces for AI agents.
• Evaluate, select, and operationalize LLM frameworks and orchestration platforms (e.g., LangChain, LangGraph, CrewAI, n8n, or custom solutions) for production-grade agentic systems.
• Implement guardrails, evaluation harnesses, and feedback loops to ensure AI agent outputs are accurate, safe, and continuously improving.
• Champion the adoption of AI-assisted development and operations practices across the SRE and broader engineering organization.

Incident Management & Root Cause Analysis

• Support the operations team’s incident response efforts, conduct post-mortems, and identify root causes to prevent recurrence.
• Leverage AI tools to accelerate incident timelines, auto-generate post-mortem drafts, and surface patterns across historical incidents.
• Document and share lessons learned, contributing to a culture of continuous improvement.

Automation & Toil Reduction

• Identify repetitive operational workflows and engineer AI-augmented or fully automated replacements.
• Build self-service tools and chatbot interfaces that allow engineering teams to query system status, retrieve logs, and execute standard operating procedures through natural language.
• Measure and report on toil reduction metrics to quantify the impact of automation initiatives.

Collaboration & Cross-functional Support

• Work closely with developers, architects, and data/ML engineers to design solutions that improve reliability and leverage AI capabilities.
• Collaborate with DevOps and NOC teams to support the application platform.
• Communicate SRE practices, AI/automation capabilities, and operational insights to technical and non-technical stakeholders.
• Provide feedback on application performance, potential improvements, and observability metrics.

Why This Role Is Different

This is not a traditional SRE position with AI bolted on as an afterthought. We are building a team that treats AI and agentic automation as core competencies—on par with Kubernetes expertise or observability design. You will have the autonomy to experiment with cutting-edge AI tools, the backing of leadership to deploy them in production, and a mandate to measurably reduce operational toil through intelligent systems.