Top Cyber Security Jobs

Develops enterprise cloud and application security architecture, roadmaps, reference architectures, and lifecycle controls. Advises infrastructure, application, business, and security teams; evaluates security technologies; designs IAM, SIEM, monitoring, analytics, scanning, and penetration-testing solutions; leads proof-of-concept evaluations; and provides strategic and solutions architecture guidance across cloud and on-premises environments.

Defines and advances enterprise security architecture across corporate, network, cloud, and application environments. Owns Zero Trust, network segmentation, IAM, firewall, remote access, SIEM, detection, SOC tooling, EDR, vulnerability management, cloud security, application security, data protection, and AI security architectures. Establishes reference standards, roadmaps, and secure-by-design practices while partnering with engineering, Security Operations, and GRC. Translates telecommunications regulations and business risks into auditable technical designs and communicates architecture to technical and executive stakeholders.

Tests AI/ML applications for vulnerabilities, adversarial threats, privacy risks, and AI-assisted attack exposure. Develops testing plans, executes authorized security assessments, analyzes results, documents findings, recommends defensive controls, and communicates remediation guidance to technical and government stakeholders. The role supports secure AI/ML implementation and federal cybersecurity programs across junior, mid-level, and senior assignments.

Designs and operates cloud security architectures, controls, guardrails, and automation across AWS and Azure. Secures AI/ML platforms, data environments, CI/CD pipelines, and infrastructure-as-code deployments. Leads threat modeling, security assessments, compliance validation, incident response support, and secure technology adoption. Partners with engineering, infrastructure, AI, data, and enterprise architecture teams while developing security standards and applying frameworks such as NIST, CIS, and Zero Trust.

Lead fomo’s application security program through architecture reviews, threat modeling, secure SDLC implementation, code reviews, penetration testing, vulnerability management, security tooling, and incident response. Establish authentication, authorization, API security, and data protection standards; manage pentest and bug bounty relationships; mentor engineers; and define the AppSec roadmap and metrics.

Lead the SBA’s AI security program as a senior subject matter expert. Develop AI security policies, risk assessments, testing frameworks, governance documentation, and lifecycle controls aligned with federal requirements. Assess threats such as model poisoning, adversarial attacks, prompt injection, and data leakage. Advise AI, data science, privacy, legal, and leadership teams; support secure MLOps, generative AI governance, training, incident reviews, and interagency engagements.

Leads enterprise application security and secure SDLC initiatives, embedding vulnerability scanning, security gates, security-as-code, and AI security controls across CI/CD pipelines. Oversees vulnerability triage, remediation SLAs, threat modeling, secure code reviews, developer enablement, security metrics, toolchain automation, software supply chain security, and AI governance. Partners with engineering, architecture, delivery enablement, and risk teams to establish secure development standards and reduce application and AI-related security risks.

Owns the enterprise strategy, roadmap, and delivery of AI security products and capabilities. Translates AI risks, regulatory requirements, and security controls into product requirements, governance tooling, access controls, observability, policy enforcement, and secure AI lifecycle workflows. Partners with cybersecurity, engineering, architecture, data, legal, risk, and governance teams to launch scalable capabilities, establish success metrics, manage adoption, and communicate progress to senior stakeholders.

Owns company-wide AI security by assessing tools, models, agents, and integrations; identifying prompt injection, data leakage, and misuse risks; implementing access, DLP, logging, and monitoring controls; partnering with Engineering on secure AI design; maintaining threat models, standards, risk tiers, inventories, and incident response playbooks; and advising teams on safe AI adoption.

Define and implement enterprise cloud and AI security architecture across AWS, Azure, and/or GCP. Secure generative AI, LLMs, agents, RAG, APIs, cloud-native workloads, containers, Kubernetes, and serverless services. Establish IAM, Zero Trust, data protection, DLP, DevSecOps, and Infrastructure-as-Code controls. Lead threat modeling, security assessments, governance, roadmap development, technology evaluations, and security-by-design initiatives while communicating risks to engineering teams and senior leadership.

Lead offensive security assessments, penetration testing, threat modeling, and attack-surface analysis across internet-facing services, APIs, embedded systems, firmware, and device interfaces. Identify vulnerabilities, guide remediation, validate fixes, and shape secure product-development practices. The role also drives risk-reduction initiatives, security architecture reviews, offensive security methodology, and strategic communication with engineering and executive stakeholders.

Designs, deploys, and operates cloud and on-premises security controls across Microsoft’s global infrastructure. Responsibilities include investigating threats and incidents, creating detections, maintaining security hardware and software, improving security policies, automating controls with infrastructure-as-code, participating in on-call support, and leading postmortems. The role focuses on Azure security technologies, network isolation, baseline enforcement, and scalable cybersecurity operations.

Lead Aircall’s detection and response program by building detection logic, SIEM data pipelines, security automation, and AI-enabled investigation tools. Own security infrastructure across AWS environments, conduct threat hunting and incident response, and improve detection maturity through documentation, tuning, metrics, and post-incident reviews. Partner with engineering, product, fraud, privacy, and legal teams while participating in on-call rotations and hiring.

Leads end-to-end security architecture for custom silicon and SoC platforms, including threat modeling, hardware roots of trust, secure boot, attestation, confidential computing, isolation, cryptographic services, secure provisioning, and physical attack resistance. Defines testable requirements and validation strategies, evaluates security IP and vendor solutions, and drives cross-functional alignment from early architecture through production and post-silicon security closure.

Lead AI security research by designing and executing attacks against LLMs, RAG systems, multimodal models, and agentic applications. Build scalable red-teaming and evaluation tooling, investigate prompt injection, jailbreaks, data leakage, model attacks, and tool abuse, and translate findings into practical mitigations. Partner with engineering, product, Responsible AI, and detection teams; evaluate defenses, map threats to MITRE ATLAS and OWASP frameworks, brief executives, publish technical reports, mentor researchers, and shape AI security methodology.

Lead security across cloud, corporate IT, physical facilities, AI systems, compliance, government authorization, and incident response. Own Google Cloud security, identity and endpoint standards, penetration testing, SOC 2, FedRAMP, NIST controls, privacy requirements, physical security, and customer trust. Build AI-native security and compliance automation, lead incident response, mentor the IT Engineer, and develop the broader security organization as the company grows.

Secures CI/CD pipelines, cloud infrastructure, software supply chains, and MLOps workflows. Builds controls for AI and LLM security, threat models AI systems, and develops internal AI agents for security automation. Partners with engineering teams on secure development practices, manages secrets and Kubernetes hardening, supports incident response, and reports on DevSecOps maturity and AI security posture.

Leads enterprise security reviews, threat modeling, architecture assessments, governance, and control development for AI, generative AI, machine learning, LLM, RAG, and AI-agent solutions. Defines security standards and guardrails, evaluates platforms and vendors, advises cross-functional stakeholders, and supports responsible AI adoption while managing cybersecurity, privacy, regulatory, and operational risks.

Own strategy and roadmap for KeeperPAM across privileged access, secrets management, secure remote access, endpoint privilege, discovery, and machine identity. Translate customer and technical needs into requirements, prioritize cross-product initiatives, partner with Engineering on integrations and architecture, conduct market analysis, define success metrics, and support go-to-market execution. The role requires strong PAM or related cybersecurity expertise, technical fluency in APIs and cloud-native DevOps environments, and effective collaboration with customers and cross-functional teams.

Designs and deploys AI-driven security automation, detection logic, and autonomous response workflows across SIEM, EDR/XDR, SOAR, and cloud platforms. Leads threat hunting, complex incident investigations, MITRE ATT&CK coverage, and protection of AI/LLM workloads. Builds Python and PowerShell security tools, integrates APIs, mentors junior engineers, and promotes software engineering best practices.

Designs and operates cybersecurity controls across identity, endpoints, networks, cloud, applications, data, and AI systems. Responsibilities include security architecture, vulnerability management, threat modeling, AI security governance, detection engineering, incident response, automation, resilience testing, compliance support, vendor evaluation, and cross-functional risk communication. The role participates in an on-call rotation and may require occasional travel to office, data-center, manufacturing, or network environments.

Leads production security engineering for AI-enabled products and platforms. Responsibilities include threat modeling, secure design and code reviews, security automation, developer tooling, authentication and authorization reviews, AI security assessments, monitoring, documentation, and remediation guidance. The role partners with engineering, product, platform, risk, and cybersecurity teams while applying AI-assisted development practices and maintaining accountability for secure, reliable, production-ready software.

Develop and mature application security practices through manual code reviews, SAST/DAST and related security tooling, penetration testing, CI/CD automation, threat modeling, and vulnerability reporting. Partner with engineering, cloud, and product teams to implement secure SDLC processes, expand Security Champions programs, secure AI/LLM features, and mentor teams on secure design and coding.

Leads ADI’s application, AI, and product security organization. Builds and scales DevSecOps and secure SDLC capabilities, AI security governance, product security, PSIRT, vulnerability disclosure, and SBOM practices. Advises the CISO, executives, and Board on quantified cyber risk; leads multidisciplinary teams, governance, incident response, regulatory alignment, and security-by-design adoption across global engineering and business organizations.

Own cloud and application security across Redox’s healthcare data platform. Responsibilities include Kubernetes and container hardening, vulnerability management, secure SDLC and CI/CD safeguards, infrastructure-as-code security, secrets management, compliance control implementation, incident response, threat modeling, design reviews, mentorship, and bug bounty triage. The role also involves securing AI workflows and collaborating with engineering teams in a fully remote, asynchronous environment.