Senior Site Reliability Engineer
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Job Description
Senior SRE maintaining Java application reliability and Kubernetes observability for Hard Rock Digital’s online sportsbook, casino, and social gaming platform. Building AI agents to automate incident response and reduce operational toil.
Responsibilities:
- Ensure availability, reliability, and performance of high-traffic Java-based applications in distributed environments
- Troubleshoot and resolve complex issues across production and non-production environments
- Conduct pre- and post-deployment performance testing and monitoring
- Optimize Java application performance through JVM tuning, efficient resource utilization, and horizontal scaling
- Deploy and manage Grafana, Prometheus, Loki, Mimir, and Alloy for monitoring, logging, and alerting
- Implement observability strategies, dashboards, alerts, and log queries
- Integrate AI/ML models for anomaly detection, predictive alerting, intelligent alert correlation, and noise reduction
- Design, build, and operate agentic AI workflows for alert triage, root cause analysis, runbook execution, and incident summarization
- Develop tool-calling LLM agents integrating with Kubernetes, Grafana, Jira, Slack, and PagerDuty
- Build and maintain MCP servers and integrations exposing internal systems to AI agents
- Evaluate and operationalize LLM frameworks and orchestration platforms for production agentic systems
- Implement guardrails, evaluation harnesses, and feedback loops for safe and improving AI outputs
- Champion AI-assisted development and operations practices across engineering
- Support incident response, conduct post-mortems, identify root causes, and document lessons learned
- Build AI-augmented automation, self-service tools, and chatbot interfaces for operational workflows
- Measure and report toil-reduction metrics
- Collaborate with developers, architects, data/ML engineers, DevOps, and NOC teams
- Communicate SRE practices, AI capabilities, and operational insights to technical and non-technical stakeholders
Requirements:
- Degree in Computer Science or a related field, or equivalent professional experience
- 5+ years in SRE, DevOps, or similar infrastructure roles with experience managing large-scale, high-availability production systems
- 3+ years hands-on experience managing production Kubernetes clusters, including deep understanding of architecture, networking, storage, and security
- Experience with cluster autoscaling (Karpenter), upgrades, and multi-cluster management
- Proficiency with kubectl, Helm, Kubernetes operators, and container orchestration troubleshooting
- Advanced expertise with the Grafana observability stack, including dashboards, alerting, visualization, and Grafana Alloy
- Proficiency in PromQL and experience with Loki for log aggregation and analysis
- Hands-on experience managing Java-based applications in distributed environments, including JVM tuning and optimization
- Cloud platform expertise; AWS preferred, with GCP or Azure also valued
- Familiarity with Infrastructure as Code tools such as Terraform/Terragrunt or Ansible
- ArgoCD proficiency for GitOps workflows and continuous deployment
- Strong scripting abilities in Python, Bash, or Go, with experience building CI/CD pipelines and deployment automation
- Proven track record with on-call rotations, incident response, and root cause analysis
- 1+ years of practical experience building or operating AI/LLM-powered tools, agents, or workflows in a production or production-adjacent context
- Ability to design agentic systems using tool calling, retrieval-augmented generation (RAG), or multi-step reasoning
- Experience integrating LLM APIs such as Anthropic Claude, OpenAI, or open-source models into backend services or automation pipelines
- Familiarity with at least one agentic orchestration framework or workflow engine, such as LangChain, LangGraph, CrewAI, n8n, Temporal, or equivalent
- Understanding of prompt engineering best practices, including structured outputs, system prompts, and few-shot examples
- Familiarity with AI-assisted coding tools such as Claude Code, Codex, or Cursor
- Experience building or consuming MCP (Model Context Protocol) servers
- Awareness of AI safety, hallucination mitigation, and human-in-the-loop design patterns
- Strong written and verbal communication skills
- Ability to mentor junior team members on traditional SRE practices and AI-driven approaches
Benefits:
- Competitive pay and benefits
- Flexible vacation allowance
- A hybrid / remote working environment
- Startup culture backed by a secure, global brand
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