Senior Operations Engineer

Job Title: ASI Senior Operations Engineer 

Team Overview:

The Attack Surface Intelligence (ASI) scanning team is responsible for building and operating the tools and infrastructure which identify potential vulnerabilities in customers’ publicly-exposed infrastructure. This involves port scanning, headless browsing, and active vulnerability scanning at various levels. The goal is to continuously improve both the breadth and depth of detection capabilities.

Job Overview:

The role is intended to be embedded in the scanning team, working closely with DevOps, Data, and Product Management to ensure the health of the ASI scanning infrastructure and application. The focus is on understanding how the application runs in the real world and ensuring it operates as intended. Additionally, the role will involve responsibilities for ensuring the reliability and performance of a data platform that includes data warehouses, data processing pipelines, and various messaging queues.

What You’ll Do: 

• Scanning Infrastructure:
• Work with Product Management to determine internal Service Level Objectives (SLOs) representing the long-term health of the scanning system (both infrastructure and application).
• Build and maintain metric collection that can feed Service Level Indicators (SLIs) to guarantee SLOs.
• Build and maintain dashboards displaying SLIs, SLOs, and other key metrics indicating the health of the application.
• Investigate cases where the scanning infrastructure or application is not performing as desired, provide guidance to the development team for improvements, and develop additional metric collection/alerting as needed.
• Identify application/deployment configuration optimizations for best use of resources and impending resource gaps.
• Work closely with DevOps to maintain and improve custom Kubernetes-based application deployment operators.
• Identify and fix automation gaps to reduce operational toil.
• Data Platform:
• Ensure the reliability and performance of the data platform, including data warehouses (Elasticsearch, ClickHouse, ScyllaDB, PostgreSQL).
• Manage and optimize data processing pipelines using Apache Spark.
• Work with messaging queues such as Apache Kafka, RabbitMQ, and Redis to ensure seamless data flow and processing.
• Develop and maintain metric collection, monitoring, and alerting for the data platform.
• Build and maintain dashboards displaying key metrics for data platform health and performance.
• Collaborate with data engineering teams to troubleshoot and resolve issues related to data storage, processing, and messaging.
• Implement best practices for data platform security, scalability, and performance.

What You’ll Bring: 

• Passion for “digging deep” and looking for “weird things” in the system that could indicate pending issues not captured in monitoring.
• Experience with one or more metrics collection tools (managed and self-hosted): Prometheus, DataDog, InfluxDB, Telegraph, VictoriaMetrics.
• Experience or desire to build visualization dashboards.
• Experience with deployment of applications within a Kubernetes environment (preferably) or containerization (Docker, etc).
• Ideally, experience with Kubernetes administration and custom operators.
• Ideally, experience with Python.
• Experience with network and vulnerability scanning tools a huge plus (nmap, zmap, masscan, nuclei, burp, NESSUS, etc).
• Familiarity with the network stack and operating system tuning: TCP/IP, conntrack, NAT, etc.
• Experience with data warehouses (Elasticsearch, ClickHouse, ScyllaDB, PostgreSQL).
• Experience with data processing pipelines using Apache Spark.
• Experience with messaging queues such as Apache Kafka, RabbitMQ, and Redis.