Top Cyber Security Jobs

Leads the strategy, development, and operation of customer-facing security analytics powered by data science and machine learning. Responsibilities include building defenses against identity, API, network, and AI-specific threats; creating automated containment mechanisms; managing security analytics roadmaps; and translating model performance, threat insights, and service-level metrics for executives and customers. The role leads security data scientists, machine learning engineers, and detection engineers across product and engineering teams.

Own the enterprise vulnerability management strategy and roadmap across infrastructure, cloud, containers, software, and AI/ML environments. Lead vulnerability response incidents, develop AI/ML security governance, automate scanning and remediation workflows, and drive threat-informed prioritization using CVSS, EPSS, and KEV. Partner with engineering, product, and architecture leaders to reduce systemic exposure, while reporting vulnerability trends, AI threats, metrics, and remediation performance to executive security leadership.

Lead penetration testing, adversary emulation, assume-breach, threat emulation, and AI red-team engagements across network, application, API, cloud, and internal infrastructure environments. Identify exploitable weaknesses, evaluate detection and response capabilities, map activity to adversary frameworks, and provide prioritized remediation guidance. The role includes client advisory, executive communication, report writing, methodology and tooling development, automation, and mentoring junior team members.

Own product security for Salesforce’s core integration and service-connectivity platform. Lead threat modeling, security design reviews, secure code reviews, and mitigation across APIs, events, messaging, connectors, service-to-service pathways, and agent integrations. Analyze Java and other-language codebases, address authorization and authentication risks, establish secure-by-default patterns, collaborate with engineering and product teams, and mentor junior security engineers.

Lead application and AI security for software systems, with primary responsibility for securing generative and agentic AI. Partner with engineering teams on threat modeling, secure design, identity and access controls, code review, CI/CD security, vulnerability remediation, and AI security guardrails. Manage red-team and penetration-testing engagements, apply security frameworks, establish standards, and mentor developers on secure coding and AI development.

Build and operate enterprise AI infrastructure for security teams, including model gateways, agent workflows, retrieval systems, evaluation, observability, and security guardrails. Drive adoption across detection, incident response, threat intelligence, vulnerability management, GRC, and security engineering. Develop production AI applications, establish governance and standards, measure impact, teach teams, and lead technical change through influence as a senior individual contributor.

Leads enterprise IT security strategy, vulnerability management, security architecture reviews, risk reporting, security tool oversight, compliance, and remediation initiatives. Advises leadership and project teams, manages security vendors, supports cloud and data center security operations, updates standards, and serves as a subject matter expert. The role requires advanced technical expertise, cross-functional leadership, executive communication, and occasional after-hours support for critical security events.

Leads UCSF’s Cyber Risk and Assurance function, directing staff and overseeing enterprise cybersecurity risk assessments, compliance reviews, exceptions, remediation, and risk acceptance. Manages GRC program operations, ServiceNow IRM workflows, metrics, policies, standards, and continuous improvement. Serves as PCI DSS subject matter expert and Internal Security Assessor, while advising senior stakeholders, auditors, vendors, and cross-functional teams on HIPAA, NIST, UC policy, and related security requirements.

Conduct vulnerability research across languages, frameworks, and architectures; reproduce and assess exploitability, reachability, and remediation correctness. Build fuzzing harnesses, datasets, graders, research tooling, and automation while improving AI agents, analysis methods, and model configurations. Lead eval-driven development by creating ground truth, adversarial cases, and regression tests. Provide technical leadership, mentor researchers, and collaborate with engineering, applied science, and product teams to improve vulnerability detection and developer remediation.

Administer security monitoring and response tools, Microsoft 365 and Azure environments, Windows Server, network equipment, patching, and vulnerability management. Support incident response, troubleshoot complex technical issues, improve IT processes, identify automation opportunities, document procedures, and lead technology projects. The role also monitors security compliance, tracks project KPIs, evaluates emerging technologies, and collaborates with technology leadership and business units.

Lead secure deployment and operation of AI and ML systems, including AI gateways, policy orchestration, security automation, and infrastructure-as-code controls. Establish an AI red-teaming program addressing prompt injection, jailbreaks, model extraction, poisoning, data leakage, and supply-chain risks. Own the AI security roadmap, advise senior leadership, apply the OWASP LLM Top 10, partner with platform teams, mentor engineers, and provide vulnerability remediation guidance.

Design and implement security across infrastructure, applications, data, and AI systems. Own authentication, authorization, tenant isolation, secure log ingestion and querying, and AI security risk mitigation. Lead security incident response and postmortems, establish practical security practices, and partner with engineering to integrate security into development. The role requires application or infrastructure security experience, knowledge of OWASP vulnerabilities, and experience securing distributed systems and APIs.

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.