Job Overview

We are seeking an experienced Senior Application Security Engineer to lead the evolution of application security across Blink. This role will define security strategy, influence engineering architecture, and build scalable security capabilities that enable developers to ship secure software quickly.

You will partner closely with engineering, platform, AI, and product teams to embed security into every stage of the software development lifecycle. In addition to securing traditional web, API, and mobile applications, you will play a key role in enabling Blink’s AI adoption by developing secure patterns for LLM-powered applications, AI agents, model integrations, and developer AI tooling.

The ideal candidate combines deep technical expertise with strong engineering judgment and the ability to influence teams across the organization.

Application Security Leadership

• Define and drive Blink’s application security strategy across web, API, mobile, and cloud-native applications.
• Lead security architecture reviews for high-impact products and critical engineering initiatives.
• Design scalable security controls that reduce risk without slowing engineering velocity.
• Establish secure engineering standards and reference architectures used across multiple engineering teams.
• Drive adoption of secure-by-default development practices throughout the SDLC.

Secure Development & DevSecOps

• Mature and automate SAST, DAST, Software Composition Analysis (SCA), IaC scanning, secrets detection, and container security.
• Build security automation integrated into CI/CD pipelines.
• Define risk-based vulnerability management processes that prioritize exploitable issues over raw findings.
• Partner with platform engineering to build reusable security services and developer self-service capabilities.
• Measure and continuously improve security engineering effectiveness using meaningful metrics.

AI Application Security

Lead security reviews for AI-powered applications, LLM integrations, AI agents, MCP-based architectures, and retrieval-augmented generation (RAG) systems.Develop secure design patterns for prompt handling, model access, tool permissions, context isolation, and AI data protection.Assess risks including prompt injection, indirect prompt injection, insecure tool use, model abuse, excessive agency, data leakage, and supply chain risks.Partner with AI engineering teams to implement guardrails, model governance, runtime monitoring, and secure AI deployment patterns.Establish security guidance for AI coding assistants and developer AI workflows.

API & Platform Security

• Lead architecture reviews for APIs and distributed systems.
• Develop organization-wide API security standards covering authentication, authorization, service identity, secrets management, and runtime protections.
• Improve visibility into API attack surface and continuously evaluate emerging API threats.

Threat Modeling & Offensive Security

• Lead threat modeling exercises for critical business initiatives.
• Perform deep security reviews and targeted penetration testing of high-risk applications.
• Partner with engineering teams to remediate complex design-level vulnerabilities.
• Develop reusable attack playbooks and security testing methodologies.

Engineering Partnership

• Act as the trusted security advisor for engineering leadership.
• Influence technical roadmaps through architecture guidance rather than policy enforcement.
• Mentor application security engineers and security champions across engineering.
• Drive security adoption through practical engineering solutions.

AI-Enabled Security Operations

• Leverage AI to improve security engineering productivity, including:
• Automated code review assistance
• AI-assisted threat modeling
• Vulnerability triage and prioritization
• Security documentation generation
• Secure code remediation recommendations
• Continuously evaluate emerging AI security tooling and identify opportunities to improve security operations through responsible AI adoption.

Security Metrics & Governance

• Define application security KPIs and executive reporting.
• Develop security standards, reference architectures, and engineering guidance.
• Measure security program maturity and continuously improve engineering security posture.

Required Qualifications

• Bachelor’s degree in Computer Science, Cybersecurity, or related field.
• 8–12+ years of experience in Application Security, Product Security, or Security Engineering.
• Demonstrated experience securing large-scale cloud-native applications.
• Strong understanding of secure software architecture and modern development practices.
• Expertise with OWASP Top 10, API Security Top 10, Mobile Top 10, and common software attack techniques.
• Experience with:
• SAST
• DAST
• Software Composition Analysis
• Container security
• Infrastructure as Code security
• Secrets management
• Strong understanding of OAuth2, OIDC, JWT, mTLS, and modern authentication mechanisms.
• Hands-on programming experience in one or more languages such as Python, Java, JavaScript, Go, or C#.
• Experience building or automating security tooling using scripting or APIs.
• Experience performing threat modeling and architecture reviews.
• Strong communication skills with demonstrated ability to influence senior engineering stakeholders.

Key Competencies

• Strategic thinker who can balance risk reduction with engineering velocity.
• Strong technical leadership without formal authority.
• Excellent architectural and systems thinking.
• Ability to influence engineering organizations through collaboration and data.
• Passion for automation and eliminating repetitive security work.
• Curiosity for emerging technologies, particularly AI, and a commitment to leveraging AI responsibly to improve security outcomes.
• Strong mentoring and coaching skills.
• Ability to simplify complex security concepts for engineers and executives alike.