Job Title: Site Reliability/Cloud Engineer

Job Summary

• Collaborate with development teams, product owners, and stakeholders to define, enforce, and track SLOs and manage error budgets.
• Improve system reliability by designing for failure, testing edge cases, and monitoring key metrics.
• Boost performance by identifying bottlenecks, optimizing resource usage, and reducing latency across services.
• Build scalable systems that handle growth in traffic or data without compromising performance.
• Stay directly involved in technical work, contributing to the codebase and leading by example in solving complex infrastructure challenges

• Design and implement scalable deployment strategies optimized for large language models like, Llama, Claude, Cohere and others.
• Set up continuous monitoring for model performance, ensuring robust alerting systems are in place to catch anomalies or degradation.
• Stay current with advancements in MLOps and Generative AI, proactively introducing innovative practices to strengthen AI infrastructure and delivery.

• Set up monitoring and observability using Prometheus, Grafana, CloudWatch, and logging with OpenSearch/ELK                                                                                                  
• Proactively identify and resolve issues by leveraging monitoring systems to catch early signals before they impact operations.
• Design and maintain alerting mechanisms that are clear, actionable, and tuned to avoid unnecessary noise or alert fatigue.
• Continuously improve system observability to enhance visibility, reduce false positives, and support faster incident response.
• Apply best practices for alert thresholds and monitoring configurations to ensure reliability and maintain system health.

• Monitor infrastructure usage to identify waste and reduce unnecessary spending.
• Optimize resource allocation by using right-sized instances, auto-scaling, and spot instances where appropriate.
• Implement cost-aware design practices during architecture and deployment planning.
• Track and analyze monthly cloud costs to ensure alignment with budget and forecast.
• Collaborate with teams to increase cost visibility and promote ownership of cloud spend.

Required Skills & Experience:

• Strong experience as SRE with a proven track record of managing large-scale, highly available systems.
• Knowledge of core operating system principles, networking fundamentals, and systems management.
• Strong understanding of cloud deployment and management practices
• Hands-on experience with Terraform/OpenTofu, Helm, Docker, Kubernetes, Prometheus and Istio
• Hands-on experience with tools and techniques to diagnose and uncover container performance
• Skilled with AWS services both from technology and cost perspectives
• Skilled in DevOps/SRE practices and build/release pipelines
• Experience working with mature development practices and tools for source control, security, and deployment
• Hands on experience with Python/Golang/Groovy/Java
• Excellent communication skills, written and verbal
• Strong analytical and problem-solving skills

Preferred Qualifications

• Experience scaling Kubernetes clusters and managing ingress traffic.
• Familiarity with multi-environment deployments and automated workflows.
• Knowledge of AWS service quotas, cost optimization, and networking nuances.
• Strong troubleshooting skills and effective communication across teams.
• Prior experience in regulated environments (HIPAA, SOC2, ISO27001) is a plus