Senior Site Reliability Engineer

We’re a fast-moving AI Security Company building AI-native infrastructure and applications powered by LLMs and autonomous agents. Our stack is deeply integrated with AWS, Kubernetes, and OpenAI-based systems, and we’re rethinking reliability in a world where software can reason, adapt, and self-heal.

We’re hiring a Senior SRE Engineer to own reliability across our cloud-native and AI-driven platform. You’ll work at the intersection of distributed systems, Kubernetes operations, and LLM-powered automation, building systems that don’t just scale—but think and fix themselves.

• 5+ years in SRE / DevOps / Platform Engineering.
• Strong hands-on experience with:
• AWS infrastructure at scale
• Kubernetes (production-grade clusters)
• Proven ability to debug complex distributed systems under pressure.
• Strong coding skills (Python or Go)—you build internal platforms and tools.
• Experience implementing monitoring, alerting, and incident management systems.

Bonus (AI / LLM Focus)

• Experience working with LLM APIs such as the OpenAI API.
• Familiarity with agent frameworks like:
• LangChain
• AutoGen
• Built or experimented with:
• AI agents for DevOps / SRE workflows
• Retrieval-Augmented Generation (RAG) systems
• Vector databases (Pinecone, Weaviate, etc.)
• Exposure to AIOps or intelligent automation systems.

• Own uptime, reliability, and performance of services running on AWS + Kubernetes (EKS).
• Design and implement self-healing infrastructure using automation and AI agents.
• Build LLM-powered operational tooling using APIs such as the OpenAI API for:
• Intelligent alert triage
• Incident summarization
• Root cause analysis
• Runbook automation
• Manage and scale Kubernetes workloads:
• Deployments, autoscaling, resource optimization
• Cluster reliability and cost efficiency
• Build and evolve observability systems:
• Metrics (Prometheus), dashboards (Grafana)
• Logs (ELK / OpenSearch)
• Tracing (OpenTelemetry)
• Define and enforce SLOs, SLAs, and error budgets tied to business metrics.
• Automate infrastructure using Terraform and CI/CD pipelines.
• Lead incident response, postmortems, and continuous reliability improvements.
• Introduce chaos engineering practices to proactively test system resilience.