BreachLock is standing up a new Reliability Engineering team and we are looking for a motivated SRE to join at the ground floor. Working alongside a Senior SRE and the Reliability Lead, you will help build the observability, monitoring, and operational foundations that underpin BreachLock's PTaaS and vulnerability management products.
This role is grounded in core SRE practice — alert triage, incident response, runbook authoring, and operational automation. As you grow into the role, you will also gain exposure to our internal AI-powered support automation system built on a RAG architecture, with mentorship from the Senior SRE.
If you are curious, technically sharp, and want to grow into a senior SRE or platform engineering role within a cybersecurity product company, this is the right environment.
Platform Monitoring & Incident Response
- Monitor and triage alerts from Grafana Cloud, Checkly, and load balancer logs; escalate per defined runbooks
- Participate in the on-call rotation as a supporting responder; document incident observations for post-incident reviews
- Assist in maintaining availability and performance dashboards covering uptime, HTTP error rates, and API latency (p50/p95/p99)
- Monitor scan job success rates, PTaaS report delivery timelines, and auth success rates; proactively flag anomalies
- Contribute to writing and maintaining runbooks and operational playbooks under Senior SRE guidance
Automation & Engineering Support
- Automate recurring operational tasks using Python scripts and Bash to reduce manual toil for routine checks and alert responses
- Assist with OpenTelemetry instrumentation tasks on Python (Django/Flask) and Node.js services
- Support deployment validation and rollback procedures in CI/CD pipelines (GitHub Actions / Cloud Build)
- Maintain documentation for infrastructure configuration, alert thresholds, and incident log history
- Actively participate in weekly team syncs, reliability reviews, and learning sessions with the Senior SRE
Requirements
Cloud & Infrastructure
- 2–3 years of hands-on experience with GCP or a major cloud provider (AWS, Azure); GCP strongly preferred
- Comfort with Linux command line, basic networking (DNS, TCP/IP, HTTP), and cloud compute fundamentals
- Working knowledge of containerization with Docker; basic Kubernetes concepts; GKE exposure is a plus
Monitoring & Observability
- Hands-on experience with at least one monitoring platform (Grafana, Datadog, CloudWatch, or equivalent)
- Ability to read and interpret dashboards, understand alert configurations, and identify metric anomalies
- Basic understanding of log aggregation and structured logging; exposure to Loki or ELK is a bonus
Development & Scripting
- Working proficiency in Python scripting for automation and operational tooling
- Familiarity with Git version control and pull request workflows
- Basic understanding of REST APIs and HTTP; exposure to GraphQL is a plus
Soft Skills
- Strong written communication — clear incident updates, runbook entries, and status reports
- Eagerness to learn SRE principles — SLOs, error budgets, toil reduction — and absorb new technologies quickly with mentorship
Calm under pressure during incident response; follows process and asks good questions
NICE TO HAVE
- Familiarity with AI / LLM concepts — understanding of how large language models are queried and integrated into applications
- Exposure to RAG (Retrieval-Augmented Generation) systems — how embedding pipelines, vector databases (ChromaDB, Pinecone, or equivalent), and LLM response generation fit together
- Any hands-on experience with vector databases or LLM APIs (OpenAI, Anthropic, or open-source models) through coursework, personal projects, or internship
- Google Cloud Associate Cloud Engineer certification or currently in-progress
- Understanding of cybersecurity concepts or experience in a security-adjacent product environment
- Exposure to Terraform at a basic level (reading/modifying existing configurations)
Experience with Checkly, Prometheus, or Grafana Cloud stack in any capacity
