Top Cybersecurity Jobs

Lead enterprise sales across the Northeast healthcare market, expanding existing accounts and winning Fortune 500 customers. Manage land-and-expand campaigns from proof of concept through deployment, exceed enterprise quotas, build channel partnerships, generate pipeline, present product demonstrations, and represent Claroty at industry events. The role focuses on cybersecurity and cyber-physical systems protection for medical and clinical environments and requires 50% travel.

Own and expand a focused portfolio of Fortune 500 and highly regulated enterprise accounts. Build executive relationships with CISOs, application security and platform engineering leaders, navigate complex buying committees, displace incumbent vendors, and execute multi-year account expansion strategies. The role requires disciplined pipeline and forecast management, strategic account planning, competitive enterprise software or security sales experience, and autonomous execution across complex, multi-stakeholder sales cycles.

Supports Navy Risk Management Framework authorization and Assessment and Authorization efforts by developing and reviewing RMF packages, tracking artifacts, analyzing information assurance problems, assessing security solutions, reviewing vulnerability and risk analyses, and improving cybersecurity processes. The role requires collaboration with Navy organizations, technical documentation, lessons-learned reporting, and onsite support in Suffolk, Virginia.

Own full-cycle technical recruiting for engineering roles: source candidates, manage interviews, collaborate with CEO and hiring managers, work with agencies, and run in-person San Francisco sourcing events to build a high-quality pipeline and close hires.

Lead technical pre-sales engagements for DevOps and platform engineering prospects. Conduct discovery, design and build custom AI agents, deliver demos and proofs of concept, assess infrastructure, develop ROI and migration plans, handle technical objections, and coordinate handoffs to onboarding and engineering teams. The role requires strong cloud, Kubernetes, Terraform, CI/CD, AI tooling, security, compliance, scripting, presentation, and solution architecture expertise.

Leads systems engineering activities for complex defense and intelligence systems, including requirements analysis, architecture and design, functional allocation, interface management, integration and test planning, risk management, technical documentation, and configuration control. Develops DoDAF and SOA architectures, supports JCIDS and certification processes, and ensures system requirements, security mechanisms, and technical deliverables meet government and program needs. Requires extensive systems engineering experience and an active TS/SCI clearance with polygraph.

Leads technical relationships with channel partners, supports sales opportunities, delivers enablement and training, develops demos and proof of concepts, and promotes Druva’s data protection solutions. The role gathers partner feedback, supports product roadmap direction, creates technical content, and drives incremental revenue through strategic partnerships. It requires deep expertise in enterprise backup, SaaS, cloud, virtualization, networking, and data protection technologies, with travel up to 25–50%.

Execute manual test cases and plans, perform functional/system/integration/regression/UAT testing, log and validate defects, collaborate with developers and stakeholders, and maintain testing documentation to ensure applications meet functional and usability requirements.

Leads the Product Security Concierge engineering team, overseeing hiring, coaching, delivery quality, capacity, utilization, managed security services, customer outcomes, and field-to-product collaboration. Reviews complex technical work involving firmware analysis, embedded penetration testing, PSIRT, compliance, and risk assessment. Establishes playbooks, service standards, SLAs, and operating models while serving as a senior technical contact for strategic customers and escalations.

Develop mathematical and computational methods to quantify information, uncertainty, redundancy, information loss, and the value of additional evidence in complex enterprise data. Apply information theory, Bayesian inference, statistics, and probabilistic modeling to build algorithms, prototypes, benchmarks, and evaluation methods for information-aware AI systems. Collaborate with research, engineering, and product teams to translate theoretical methods into practical systems.