AI-Assisted Cyber Analysis Specialist

Job Title: AI-Assisted Cyber Analysis SpecialistJob Category: Information TechnologyTime Type: Full timeMinimum Clearance Required to Start: TS/SCIEmployee Type: RegularPercentage of Travel Required: Up to 10%Type of Travel: Continental US* * *

The Opportunity:

CACI is seeking an AI-Assisted Cyber Analysis Specialist to design and operate governed workflows for large-scale code, configuration, scan-result, and security-artifact triage. This is an applied cyber-analysis role, not a generic data-science position. The specialist will combine security expertise, Python automation, approved AI/ML or agentic workflows, and human validation to accelerate analysis while preserving accuracy, provenance, confidentiality, and reproducibility.

This position will provide continuous technical assessment support for full‑time, proactive testing of externally and internally visible federal cyber assets. This expands federal visibility by conducting continual assessments of .gov domains, subdomains, and internet‑facing assets to uncover unknown exposures, validate vulnerabilities, and provide agencies with actionable remediation guidance. This role supports the Continuous Diagnostics and Mitigation (CDM) Program’s mission to safeguard and secure cyberspace in an environment where the threat of cyber-attack is continuously growing and evolving and is responsible for enhancing the security, resilience, and reliability of the Nation’s cyber and communications infrastructure. The CDM Program defends the United States (U.S.) Federal Information Technology (IT) networks from cybersecurity threats by providing continuous monitoring sensors (tools), diagnosis, mitigation tools, and associated services to strengthen the security posture of Government networks.

Responsibilities:

• Design human-in-the-loop AI-assisted workflows to classify, enrich, correlate, summarize, and prioritize large volumes of code, configurations, scan results, findings, evidence, and other cyber artifacts.

• Build Python services, tools, APIs, prompts, schemas, retrieval pipelines, and evaluation harnesses using customer-approved model endpoints and data stores.

• Integrate deterministic security tools and rules—such as SAST/DAST, Semgrep, YARA, Sigma, SBOM, vulnerability, and configuration results—with AI-assisted triage rather than relying on model output alone.

• Measure precision, recall, false-positive and false-negative rates, latency, cost, drift, and analyst time saved; document acceptance thresholds and rollback paths.

• Protect sensitive data by enforcing access controls, approved model boundaries, provenance, audit logs, redaction, prompt-injection defenses, and safe handling of untrusted code and artifacts.

• Present structured findings and uncertainty to security analysts, support manual validation, and capture analyst feedback for continuous improvement.

• Maintain technical documentation, test datasets, model/workflow versions, and reproducible release processes.

Qualifications:

Required:

• U.S. citizenship is required.

• The selected candidate must meet eligibility requirements for access to sensitive information and be able to obtain a Public Trust fitness determination (High Risk).

• Ability to work in customer-provided remote environments, use customer-approved tools, and comply with rules of engagement, data-handling requirements, evidence controls, deconfliction procedures, and stop-work criteria.

• Five or more years of combined cybersecurity analysis, security engineering, software/data engineering, or applied AI/ML experience, including production automation used by analysts or operators.

• Strong Python, API, data-processing, testing, and source-control skills; experience handling structured and unstructured technical artifacts at scale.

• Practical knowledge of vulnerability assessment, attack paths, source-code or configuration analysis, malware/artifact triage, or security-tool outputs sufficient to validate analytical results.

• Experience building and evaluating AI/ML or LLM-assisted workflows with explicit human review, grounding/provenance, structured outputs, and measurable quality controls.

• Understanding of AI security risks including data leakage, prompt injection, untrusted content, model hallucination, authorization, auditability, and secure deployment.

• Ability to communicate limitations and uncertainty clearly and to produce maintainable technical documentation.

Desired:

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