AI Automation Engineer

AI/ML Automation Engineer

Location: Government Facility (Hybrid/Onsite)
Security Clearance: Active Secret Clearance Required (TS/SCI Preferred)
Customer: U.S. Department of Homeland Security (DHS)
Employment Type: Full-Time

Argo Cyber Systems is a Service-Disabled Veteran-Owned Small Business (SDVOSB) delivering advanced cybersecurity engineering, artificial intelligence, cloud security, digital forensics, threat intelligence, and cyber modernization services to Federal agencies and critical infrastructure organizations.

We are seeking an experienced AI/ML Automation Engineer to architect and implement intelligent automation capabilities that enhance cyber operations, malware analysis, digital forensics, and mission decision-making. This role combines machine learning engineering, generative AI, cloud-native development, and workflow automation to build scalable AI solutions supporting national cybersecurity missions.

The AI/ML Automation Engineer serves as the senior technical lead responsible for designing, developing, deploying, and optimizing AI-driven capabilities across cybersecurity operations.

You will collaborate with cyber analysts, data scientists, software engineers, cloud architects, and mission stakeholders to implement advanced machine learning models, Large Language Model (LLM) integrations, Retrieval-Augmented Generation (RAG) solutions, autonomous agent workflows, and intelligent automation supporting operational cyber missions.

This position offers the opportunity to shape next-generation AI capabilities used in support of incident response, malware analysis, threat intelligence, digital forensics, and cybersecurity modernization.

• Design, develop, and deploy enterprise AI and machine learning solutions supporting cybersecurity operations.
• Develop intelligent automation using LLMs, foundation models, and autonomous AI agents.
• Build Retrieval-Augmented Generation (RAG) pipelines for secure knowledge retrieval.
• Design prompt engineering strategies and optimize AI model performance.
• Develop feature engineering, data preparation, and ML training pipelines.
• Support model evaluation, tuning, validation, and continuous improvement.

• Design end-to-end automation workflows for cyber operations.
• Automate malware collection, detonation, classification, and analysis.
• Build AI-driven orchestration supporting incident response and digital forensics.
• Develop APIs enabling secure data exchange between cyber platforms.
• Automate repetitive analytical processes to improve operational efficiency.

• Design cloud-native AI solutions using AWS services.
• Develop AI integrations utilizing Amazon Bedrock and foundation models.
• Implement scalable ML pipelines using Databricks and cloud data platforms.
• Deploy containerized AI workloads using Docker and Kubernetes.
• Build CI/CD pipelines supporting rapid AI model deployment.

• Design and maintain scalable data ingestion pipelines.
• Build data transformation, normalization, and enrichment workflows.
• Develop streaming data integrations supporting AI workloads.
• Optimize data quality, governance, and operational performance.
• Support structured, semi-structured, and unstructured data processing.

• Develop AI-enabled malware analysis capabilities.
• Support AI-driven threat intelligence enrichment.
• Build detection engineering automation.
• Develop machine learning capabilities supporting digital forensics.
• Assist cyber analysts by integrating AI decision-support capabilities into operational workflows.

• Provide technical leadership for AI modernization initiatives.
• Mentor engineers on AI engineering best…