- B2B
- Scale StageRapidly increasing operations
- Top InvestorsThis company has received a significant amount of investment from top investors
- +2
Staff Engineer - Platform Security
- Remote •
- Full Time
About the job
About Abnormal Security:
Abnormal Security is defining the next generation of email security defense. Our platform uses machine learning and artificial intelligence to baseline communication content, user identity, and behavioral signals in real-time and at-scale in order to detect the abnormalities of email attacks.
Customers love us because we consistently detect and stop what everyone else in the market can’t -- advanced attacks that have never been seen before -- and we do so with beautiful user interfaces and best-in-industry customer support.
Our veteran team has built some of the most enduring machine learning platforms at leading companies including Google, Twitter, Pinterest, Amazon, Microsoft, and Expanse. We are located in San Francisco,CA, New York, NY and Lehi, UT.
Our company is growing - we’re on the Forbes AI 50, and a Gartner 2020 Cool Vendor, and our customer base includes multiple Fortune 500 companies.
The Opportunity
We are looking for a key member of the platform security team for the newest cybersecurity unicorn company. Driving the security and privacy practice of our platforms and products, you will provide technical guidance and mentorship to the team. You champion security efforts across multiple engineering teams, and the whole company, contributing to the roadmap and the success of the company.
Who you are:
Experienced security engineer, led a strong engineering team, mentored both IC engineers and tech leads, and identified ways to improve platform and infrastructure security.
Experienced tech lead, worked closely with other senior members across the company to set the vision and roadmap of platform and infrastructure security and privacy
What you’ll do:
Be one primary driver of security efforts within engineering for our platform and infrastructure teams
Advocate security and privacy within the engineering organization, establishing frameworks and services to secure our products and systems
You will collaborate closely with every engineering team to lead high-quality designs, coding, and tools for security & privacy
You will identify, design, and implement the best security practices within all our products and projects.
Opportunities to help build and mentor a dedicated security team
Experience you’ll need:
8+ years of software development experience
4+ years of experience leading technology decisions for engineering infrastructure
Bachelor’s degree or equivalent practical experience in software engineering
Experience as tech lead for security and privacy engineering team
Plus if there is experience with developing from ideas to products
Plus if there is experience with ML or security products
Track record of leading high-quality designs, code, tools, and security systems.
Experience with one or more of the
AppSec focused - working to secure our product and platforms
Vulnerability & Risk Assessments, Threat Detection, Incident Response, etc.
Working with PenTest teams, bug-bounty programs
Evaluating Zero Days
Interpreted Programming Language or Scripting: Python, Perl, Bash, Go, Ruby, PHP, etc.
Authentication, encryption, cryptography, security protocols, monitoring, IDS/IPS
Experience with DevSecOps tooling, OWASP, OAuth
Experience with mentoring junior engineers, and working across multiple teams
Enterprise SaaS/ Cybersecurity background a plus
Abnormal Security is committed to creating a diverse work environment. All qualified applicants will receive consideration without regard to race, religion, gender, gender identity, sexual orientation, national origin, genetics, disability, age, or veteran status.
About the company
- B2B
- Scale StageRapidly increasing operations
- Top InvestorsThis company has received a significant amount of investment from top investors
- Valuation $1B+This company has a valuation of $1B or more
- Recently fundedRaised funding in the past six months