Network Simulation Dev/Test Engineer - Top Secret Clearance (SCI Eligible)

Full-time

Description

The Network Simulation Dev/Test Engineer supports test and evaluation efforts by generating simulated network traffic—including normal, anomalous, and malware traffic patterns—while collecting and analyzing data with AI-powered tools. This role involves automating Linux processes, managing Docker environments for AI/ML workflows, building dashboards with the ELK stack, and applying deep knowledge of network vulnerabilities. The position supports RMF compliance and provides technical documentation for stakeholders, with an emphasis on improving the reproducibility of AI-driven testing pipelines.

Primary Place of Performance: Springfield, VA 22151
Travel: Up to 20% CONUS & OCONUS travel
Mandatory Requirements: U.S. Citizenship and TS/SCI Clearance
Years of Experience: 5–10 years

Responsibilities

AI/ML Traffic Simulation & Data Collection

• Set up traffic generators to simulate normal corporate traffic, anomalous activity, and malware patterns using AI/ML techniques.
• Collect, organize, and analyze packet capture (PCAP) data using Arkime, AI models, and maintaining structured PCAP directories.
• Develop repeatable AI-driven test environments to evaluate network monitoring and detection capabilities, utilizing machine learning for anomaly detection.

Automation & System Operations

• Automate Linux processes with shell scripts for scheduling, initializing containers, and running Python-based AI/ML workflows.
• Manage Docker environments for testing and deployment of network monitoring and AI/ML tools.
• Integrate automation into AI/ML test pipelines to improve efficiency, model reproducibility, and optimization

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AI/ML Security Operations & Vulnerability Analysis

• Apply AI/ML models to understand and simulate network vulnerabilities and attack vectors.
• Support cyber defense teams by using AI techniques for adversarial testing, including simulating malware traffic.
• Utilize the ELK stack (Elasticsearch, Logstash, Kibana) to visualize network data and AI-based traffic patterns.
• Contribute to vulnerability detection and incident response using machine learning-powered tools.

Compliance & Documentation

• Support and facilitate Risk Management Framework (RMF) compliance, ensuring AI/ML workflows meet security standards.
• Develop and maintain SOPs, AI-enhanced network/system diagrams, and technical baselines.
• Provide technical recommendations and findings to leadership, ensuring AI-driven solutions align with organizational goals.

Requirements

Experience

• 5+ years in cybersecurity, network operations, AI/ML systems engineering, or related roles.
• Experience architecting and managing networking infrastructure to support AI/ML pipelines, including configuring taps and packet brokers, integrating traffic generators for performance testing, and deploying network visibility/monitoring tools such as Arkime within secure DevOps environments.
• Provide cyber analytics consulting to AI/ML developers by leveraging expertise in networking and cybersecurity, advising on attack vectors, common threats, and vulnerabilities, and serving as a bridge to translate operational security insights into AI/ML development requirements and pipeline designs.
• Hands-on experience with traffic generation, PCAP analysis, and integrating AI/ML techniques for network data analysis.
• Familiarity with Arkime, Zeek, Suricata, and similar network analysis platforms, with a focus on machine learning integrations.
• Experience building AI/ML dashboards with Kibana or other SIEM/visualization platforms.

Technical Skills

• Strong Linux administration, shell scripting, and experience with AI/ML automation using Python.
• Familiarity with containerized environments using Docker for AI/ML workflows.
• Understanding of AI/ML concepts, including network traffic analysis, vulnerability detection, and anomaly detection with machine learning.
• Knowledge of attack vectors, malware behaviors, and adversary TTPs, with applications for AI-driven simulations.

Communication

• Strong written and verbal communication skills, with the ability to explain technical AI/ML concepts to both technical and non-technical audiences.
• Ability to develop clear, concise documentation for AI/ML models, network analysis, and security protocols.

Preferred Education, Experience, & Skills

• Bachelor's or master's degree in computer science, Cybersecurity, AI/ML, or related field.
• Minimum DoD 8140 IAT Level II certification or equivalent highly desired (Or obtain within 6 months from hire).
• Minimum DoD 8140 CSSP Auditor certification or equivalent highly desired (Or obtain within 6 months from hire).
• Advanced certifications (e.g., OSCP, GCIA, Elastic Certified Engineer, Certified TensorFlow Developer).
• Experience with cloud platforms (AWS, Azure, or GCP) for deploying AI/ML solutions at scale.

Competitive Benefits Package Includes

• 100% employer-paid medical, dental, and vision for employees and dependents.
• 401(k) with 3% company contribution and immediate vesting.
• Generous PTO policy (15 vacation, 5 sick, 2 personal days).
• Reimbursement for job-related certifications, annual training budget, and company-provided access to training platforms.

JFL Consulting, LLC is an Equal Opportunity Employer.
We do not discriminate against any applicant for employment on any legally recognized basis including, but not limited to: race, religion or creed, color, national origin, sex, age, disability, marital status, sexual orientation, genetic information, veteran status, or any other protected class under federal, state, or local statute. It is also the policy of JFL Consulting, LLC to provide reasonable accommodations for qualified individuals with disabilities.