Manager, Security Engineering

Acquia; Deutschland; Vor Ort; EUR 131.394 - 148.694; Vollzeit

Benefits dieser Stelle

Competitive healthcare coverage

Wellness programs

Generous parental leave

Take-it-when-you-need-it time off

Zusammenfassung

jobr.pro is seeking a Manager of Security Engineering to lead a dedicated team focusing on application, cloud, and AI system security. This role involves proactively identifying systemic security gaps and establishing automated controls to secure services across AWS.

The ideal candidate will possess hands-on experience with security tooling and a deep understanding of cloud security. jobr.pro offers competitive healthcare coverage, wellness programs, and a supportive work environment.

Qualifikationen

• Hands-on experience with SAST, DAST, and SCA tooling.
• Deep understanding of securing cloud-native applications on AWS.
• Working knowledge of OWASP LLM Top 10 and AI attack surfaces.
• Experience with AI-assisted security tools.
• Strong knowledge of compliance frameworks like ISO/SOC.

Aufgaben

• Lead a specialized team of security engineers.
• Manage, mentor, and grow a team.
• Define and execute a security engineering roadmap.
• Champion shift-left security practices.
• Lead research spikes to identify security gaps.

Kenntnisse

Application Security

Cloud Security

AI Security

AI Tooling

Compliance Acumen

Communication Skills

Tools

SAST

DAST

SCA

Jobbeschreibung

Role Overview

As the Manager of Security Engineering, you lead a specialized team of security engineers focused on application security, cloud security, and AI system security across Acquia's product portfolio. Operating on an evidence-based engineering model, your team proactively researches and identifies systemic security gaps to build automated controls and guardrails. By securing cloud-native applications and services across AWS, you enable Acquia's Product teams to inherit a “secure by default” foundation. You act as the critical nexus between Security Operations and Product Engineering, translating complex technical risks into actionable roadmaps that align with overarching business objectives—including the secure adoption of AI technologies.

Team Leadership & People Management

• Manage, mentor, and grow a dedicated team of security engineers.
• Conduct continuous performance evaluations (quarterly and annually) to guide professional development and advocate for promotions.

Technical Strategy & Roadmap Execution

• Define and execute a forward-looking security engineering roadmap aligned with Product Engineering needs and broader business initiatives, including the secure enablement of AI technologies.
• Translate high‑level business direction into actionable quarterly deliverables for the team.
• Establish and measure team success against the completion of quarterly goals and the continuous improvement of annual compliance audit results.

Application Security & Secure SDLC

• Champion shift‑left security practices, including threat modeling, secure code review, and developer security training embedded in the software development lifecycle.
• Own and scale application security tooling—SAST, DAST, and SCA platforms—to systematically surface and remediate vulnerabilities across product codebases.
• Shift the security paradigm from manual operational cleanup to building automated solutions and guardrails that eliminate entire classes of vulnerabilities.

Evidence‑Based Engineering & Cloud Security Architecture

• Lead “research spikes” to proactively investigate cloud‑native environments and identify systemic security gaps before they become incidents.
• Ensure all security initiatives are rooted in clear findings and deliver exact, architectural fixes (code or configuration) to resolve them.
• Define and enforce cloud security standards spanning IAM, API security, secrets management, and container workloads across AWS environments.

Agentic AI & LLM Security

• Define and enforce security standards for internal enterprise AI systems, including LLM‑based agents, RAG pipelines, and AI‑integrated workflows—covering risks such as prompt injection, data exfiltration, and privilege escalation.
• Lead threat modeling for agentic AI systems where models have access to tools, APIs, or sensitive data.
• Partner with AI/ML engineering teams to embed security review into AI development lifecycles, from model selection through deployment.
• Evaluate and deploy AI‑native security tooling to augment the team’s detection, triage, and remediation capacity.

Cross‑Functional Collaboration & Influence

• Act as an internal consultant and advisory body to Product Engineering teams, guiding them on secure implementation practices.
• Communicate complex, highly technical security risks effectively to non‑technical project managers and stakeholders.
• Influence and negotiate with software developers to prioritize and remediate vulnerabilities within their workflows.
• Serve as the primary technical bridge between Product Engineering and Security Operations, providing guidance on cloud and Kubernetes security configurations.

Qualifications & Technical Requirements

• Application Security: Hands‑on experience with SAST, DAST, and SCA tooling (e.g., Semgrep, Snyk, Veracode, or equivalents) and guiding engineering teams on remediation.
• Cloud Security: Deep understanding of securing cloud‑native applications and services on AWS, including IAM, API Gateway, secrets management, and container workloads.
• AI Security: Working knowledge of OWASP LLM Top 10, agentic AI attack surfaces (tool abuse, prompt injection, memory poisoning), and security considerations for AI systems with external integrations.
• AI Tooling: Experience using AI‑assisted security tools—such as AI‑powered SAST, copilot‑assisted code review, or agentic vulnerability triage—to scale team output.
• Compliance Acumen: Strong working knowledge of the technical implications of operating within strict compliance frameworks, including ISO/SOC, PCI, and FedRAMP.
• Communication Skills: Exceptional ability to translate highly technical concepts for non‑technical stakeholders and the interpersonal skills required to influence engineering teams without direct reporting authority.

We are an organization that embraces innovation and the potential of AI to enhance our processes and improve our work. We are always looking for individuals who are open to learning new technologies and collaborating with AI tools to achieve our goals.

Acquia is proud to provide best‑in‑class benefits to help our employees and their families maintain a healthy body and mind. Core Benefits include: competitive healthcare coverage, wellness programs, take it when you need it time off, parental leave, recognition programs, and much more!

Final compensation will be commensurate with your experience and will be determined by a variety of factors, including city of residence, relevant skillset, and job‑related knowledge.

Acquia is an equal opportunity (EEO) employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veterans status or any other protected status or characteristic under federal, state or local law unrelated to the ability to perform the job.

We are seeking an AI‑Native candidate who treats AI not as an external tool, but as a fundamental extension of their cognitive workflow. The ideal candidate possesses an orchestration mindset—the ability to skillfully prompt, manage, and direct AI to navigate complexity—and maintains a high degree of AI fluency.

You should be characterized by radical adaptability and a "builder" mentality, showing a restless drive to transform traditional work processes into agentic workflows. Beyond technical proficiency, we value intellectual humility: the willingness to constantly unlearn old methods in favor of more efficient, AI‑augmented processes. You don’t just use AI to do your job; you use it to redefine what your job can achieve.

Pay Range: $150,000—$169,750 USD