Top Entry Level Cybersecurity Jobs in Atlanta, GA

Build and lead an AI-native growth marketing engine for a cybersecurity SaaS company. Develop integrated demand-generation campaigns, create pipeline, influence the full customer funnel, strengthen messaging, and coordinate with product marketing, sales, SDR, and field teams. Use data and AI to optimize marketing performance, accelerate deals, and scale effective programs while leading and developing marketers.

Generates qualified sales pipeline across a defined U.S. territory through personalized outbound prospecting. Responsibilities include researching target accounts, creating multi-channel sequences, qualifying inbound and marketing leads, booking productive meetings, maintaining Salesforce records, coordinating with ABM marketing, and partnering with account executives on territory strategy and handoffs.

Manage post-sales relationships with federal customers through onboarding, adoption, enablement, renewals, and expansion. Lead customer kickoffs, architecture planning, business reviews, success plans, feature education, and renewal-risk mitigation. Collaborate with Customer Success Engineering, Sales, Marketing, R&D, and executives to support customer goals, identify expansion opportunities, and maintain accurate customer records in Catalyst and Salesforce.

Lead brand and visual design for Cloaked’s premium concierge privacy offering. Responsibilities include developing the visual identity and guidelines, designing client onboarding presentations and product-interface concepts, creating motion and animation, producing high-touch print collateral and merchandise, and collaborating independently with the offering lead. The engagement is a four-to-six-month contract with potential full-time conversion.

Talent network opportunity for professionals interested in cybersecurity and related disciplines, including software development, security, product management, sales, marketing, customer success, business operations, and customer support. Candidates should submit a resume and cover letter specifying areas of interest. The company offers fully remote work, flexible hours, unlimited vacation, insurance, and retirement benefits.

Supports cybersecurity pre-sales engineering through customer demos and proof-of-concept engagements. Assists product marketing with technical datasheets, white papers, blogs, videos, and collateral. Researches compliance standards, security frameworks, emerging threats, and attack vectors. Participates in product testing as the voice of the customer. The role is remote and includes training in cloud platforms, Kubernetes, security tools, programming, and security research.

Manage cybersecurity incident response projects from initiation through completion, coordinating DFIR, advisory, IT, legal, HR, clients, and vendors. Responsibilities include project planning, stakeholder communication, risk and issue management, resource allocation, budgets, incident response artifacts, compliance, post-incident reviews, and continuous improvement. The role also supports cybersecurity frameworks, tools, and after-hours rotational coverage for critical incidents.

Facilitates Agile ceremonies and SAFe events for an Agile Release Train, coaches teams toward self-management, coordinates dependencies, removes impediments, tracks metrics, and promotes Lean-Agile practices. The role partners with Product Owners, Scrum Masters, RTEs, and stakeholders to support backlog refinement, PI objectives, continuous improvement, and cross-team alignment. Travel to US Navy facilities is required at least three times annually.

Consults with clients to implement, administer, customize, and support Zoho systems. Responsibilities include client engagement, training, expectation management, communications, solution implementation across Zoho One applications, workflow automation using Deluge, change management, community engagement, and content creation. Spanish fluency is required for Latin American client engagement.

Build and optimize production systems for heterogeneous machine learning models, including small models, medium models, and LLMs. Develop distributed systems for large-scale data processing, model training and validation, experimentation, deployment, and CI/CD. Ensure system robustness, scalability, and long-term maintainability while supporting data management and evolving model-development workflows.