Lumen - Lead Security Engineer
Lumen is guided by our belief that humanity is at its best when technology advances the way we live and work. With 450,000 route fiber miles serving customers in more than 60 countries, we deliver the fastest, most secure global platform for applications and data to help businesses, government and communities deliver amazing experiences. Learn more about Lumen’s network, edge cloud, security and communication and collaboration solutions and our purpose to further human progress through technology at news.lumen.com, LinkedIn: /lumentechnologies, Twitter: @lumentechco, Facebook: /lumentechnologies, Instagram: @lumentechnologies and YouTube: /lumentechnologies.
Black Lotus Labs has an opening for a lead security engineer that will leverage Lumen’s unique visibility to hunt botnets and scale discovery of evolving malicious threats in the criminal ecosystem. Our distinctive data sets as well as our computing cluster present exciting opportunities to integrate machine learning outputs and graph analytic techniques as we find new ways to hunt threats across the internet. Black Lotus Labs has detected and disrupted key evolving threats at an internet scale for years.
This position will work alongside other advanced security researchers, data scientists, data engineers, and malware reverse engineers to tackle evolving threats accelerated by technologies like our Hadoop ecosystem (HBase, HDFS, Spark, Kafka, AirFlow), Elasticsearch and Redis clusters, Docker using Docker Swarm, malware environment, and a network of honeypots.
This is a close-knit, experienced, amazingly smart team that you can be a part of and help build out. This is a remote/work-from-home opening as well available anyw in the US with travel around 2 times per year.
The Main Responsibilities
- Research latest threat attacker tools, techniques and procedures (TTPs) with a goal of automating detection
- Regularly prepare findings for technical internal and external publications.
- Analyze attacks and use forensic data and OSINT methods for investigation
- Apply strong knowledge of systems architecture and security as well as deep network and application protocol knowledge to analyze attacks and threat actor methodologies
- Automate investigations through Python scripting
- Set priority of what threats to analyze and how long to spend on them to maximize the team's impact
- Work with team to scale analysis of evolving threats and tracking threat actors in collaboration with data scientists to leverage machine learning and graph analytic outputs
- Build and maintain trust relationships with other intelligence teams, law enforcement, and other outside groups
- Support threat research customer and partner RFIs
- Work as the team point-of-contact in a rotational cycle to triage incoming research-related events
- Contribute to deliverables and performance metrics w applicable
- Act as company SME for threat actor-related issues
What We Look For in a Candidate
Desired candidates will have a strong background exhibiting:
- Experience with tracking of threat actors as part of investigations and threat research efforts
- Experience using OSINT methods for investigation
- Experiencing publishing technical reports on threat intelligence or security topics.
- Scripting experience with Python and familiarity with distributed computing
- Extensive experience hunting threat activity, particularly exploitation frameworks and ransomware toolsets
- Experience developing algorithms and techniques to identify new threats from large data sets
- Deep knowledge of network-based threats and identifying behaviors without attack payloads
- Strong analytical thinking and ability to quickly pick up new methods, tools and programming languages
- Ability to work collaboratively with closely partnered internal teams to accomplish work
- User-level experience in a Unix-based environment
- Familiarity with extracting data through SQL
- Strong writing skills to assist in sharing our knowledge with the public
Well experienced candidates may also have the following skills:
- Experience with Spark and distributed computing teams, law enforcement, and other outside groups
- Familiarity with tools for managing, analyzing, and visualizing large datasets such as Elasticsearch or Splunk
- Experience developing automation and analysis in Python-based environments
- Understanding of static or dynamic analysis of malware
- Ability to analyze large data sets and present conclusions drawn from them
- Ability to work with others in providing direction and assisting in learning new topics
- Functional knowledge of machine learning and how it can be applied to data sets
- Public speaking experience and a willingness to share technical topics in public forum