Barracuda Security Team

Open security roles at Barracuda, and what we know about the team behind them.

computer & network security · 2300 employees · 2 open roles. Updated October 15, 2026.

Open roles (2)

Barracuda

“A 'developer-focused mindset' and the integration of security directly into the engineering workflow rather than acting...”

Barracuda

“A 'developer-focused mindset' and the integration of security directly into the engineering workflow rather than acting...”

Compiled from public job postings, careers pages, and company materials. Data may not reflect current state — verify during interviews.

3 Intel Signals

How they approach application security

Barracuda's AppSec philosophy centers on a 'developer-focused mindset' and the integration of security directly into the engineering workflow rather than acting as a separate gate.
The stated AppSec mission is to 'Embed security across the development lifecycle.' The team prioritizes a risk-based approach, focusing on the 'OWASP Top 10 Web and API threats' and aims to 'Drive risk rating and vulnerability management processes.' A primary goal is to 'help shape the future of our AppSec program' through automation and lifecycle embedding.

The team

Barracuda maintains a dedicated Application Security team that includes roles such as Senior Application Security Engineers and Application Security Engineers.
The team is currently in a growth phase, actively hiring for senior positions to 'help shape the future' of the program.
Key public-facing members include Alejandro Salinas and Kevin Farrow.
Team size is estimated at 5-15 members based on public profiles and hiring activity.

What they're working on

Barracuda's AppSec initiatives focus on automating security within the CI/CD pipeline and implementing proactive threat modeling.
The team works to 'Embed security across the development lifecycle' using 'CI/CD automation tools (SAST, SCA, Secrets Scanning, etc.).' Vulnerability management utilizes 'Barracuda Active Threat Intelligence' and 'Vulnerability Manager.' Secure SDLC artifacts include 'lightweight, feature-level threat models.' Recent initiatives include integration of Machine Learning for remediation through the 'Machine Learning-powered Auto Configuration Engine.'.