Lead, Application Security

Overview 

We're building a new UAE-based business spanning Sportsbook, Casino, Lottery and a broader connected Fan Ecosystem, backed by Fanatics and Momentum. As Lead, Application Security, you'll own application security testing and DevSecOps engineering end to end across FanMo's technology platforms. 

This is a hands-on engineering leadership role. You'll be responsible for embedding security throughout the software development lifecycle, ensuring our applications, APIs, infrastructure and deployment pipelines are secure by default. You'll own the application security tooling ecosystem, engineer automated security controls into CI/CD pipelines, and build the guardrails and developer self-service capabilities that enable engineering teams to deliver securely at pace. 

With AI increasingly changing how software is built, you'll also play a key role in making AI-assisted development secure by design. This means understanding the risks introduced by AI-generated code and agentic workflows, implementing practical security controls, and helping developers use AI coding assistants safely and effectively. 

The ideal candidate combines strong software engineering fundamentals with an offensive security mindset. You're comfortable getting hands-on with code, validating vulnerabilities, automating security controls and influencing engineering teams. You know how to distinguish theoretical findings from genuine, exploitable risk and turn those insights into practical improvements. 

Responsibilities 

What You'll Own 

Application Security & Testing 

• Own FanMo's application security testing capability across SAST, DAST, IAST, SCA, secrets detection, container scanning, infrastructure-as-code scanning, API security and mobile application testing.
• Manage the full lifecycle of application security platforms, including evaluation, implementation, integration, configuration, upgrades and ongoing optimization.
• Establish application onboarding, scanning policies, security rules and testing frequency based on application risk.
• Tune existing rulesets and develop custom rules to improve accuracy and reduce false positives.
• Build a consolidated view of application security risk, prioritizing findings based on exploitability and business impact.
• Extend application security testing to AI-generated code and AI-enabled product features. 

Vulnerability Management & Developer Enablement 

• Own vulnerability triage, validation, prioritization and remediation tracking across application security findings.
• Establish automated workflows to route findings to engineering teams, track remediation against agreed SLAs and verify closure.
• Build developer self-service capabilities, including IDE integrations, secure templates, approved base images and hardened libraries.
• Provide practical, actionable remediation guidance directly to developers.
• Establish and support a security champions network across engineering teams.
• Develop secure-by-default instructions, reusable rules and skills for AI coding assistants to ensure generated code aligns with organizational security standards.
• Deliver targeted secure-coding education based on recurring vulnerabilities and root-cause analysis. 

Offensive-Informed Application Security 

• Validate high and critical vulnerabilities through hands-on testing and proof-of-concept exploitation in non-production environments.
• Conduct manual security testing of high-risk features, APIs and business logic ahead of release.
• Translate confirmed exploits and penetration-testing findings into automated regression tests.
• Design abuse-case testing for gaming-specific risks, including bonus and promotion abuse, wallet and balance race conditions, bet manipulation, account takeover and responsible-gaming control bypasses. 

Software Supply Chain Security 

• Define and implement security controls for dependency management, artifact signing, provenance verification and Software Bill of Materials (SBOM) generation.
• Assess third-party libraries, components and build dependencies for security risk.
• Address AI-specific supply chain risks, including AI-suggested or non-existent packages, third-party models, MCP servers, plugins and IDE extensions.
• Monitor newly disclosed vulnerabilities in third-party components and drive prioritized remediation across affected applications. 

Threat Modeling & Secure Software Delivery