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

About Argo Cyber

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.

Position Overview

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.

Primary Responsibilities

AI & Machine Learning Engineering

• 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.

Intelligent Automation

• 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.

Cloud AI Engineering

• 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.

Data Engineering

• 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.

Cybersecurity AI

• 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.

Collaboration & Leadership

• Provide technical leadership for AI modernization initiatives.
• Mentor engineers on AI engineering best practices.
• Collaborate with cybersecurity SMEs and software development teams.
• Develop architecture documentation, design artifacts, and technical standards.
• Present AI capabilities to executive leadership and government stakeholders.

Required Qualifications

• U.S. Citizenship
• Active Secret Security Clearance
• Ability to obtain DHS Entry on Duty (EOD) Suitability
• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Computer Engineering, or related STEM field
• Five (5) or more years of professional experience developing AI, ML, automation, or data engineering solutions
• Strong Python development experience
• Experience with Databricks AI Platform
• Experience implementing machine learning pipelines
• Experience integrating Large Language Models (LLMs)
• Experience with Amazon Bedrock and AWS AI services
• Experience building REST APIs and cloud-native applications
• Experience with Git, CI/CD pipelines, and software development best practices
• Strong analytical, problem-solving, and communication skills

Preferred Qualifications

• Active TS/SCI Clearance
• Experience supporting DHS, CISA, NSA, FBI, DoD, or Intelligence Community programs
• Experience implementing Generative AI solutions
• Experience developing autonomous AI agents
• Experience building RAG architectures
• Experience with LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar AI orchestration frameworks
• Experience with vector databases (Pinecone, FAISS, ChromaDB, OpenSearch Vector Engine)
• Experience supporting malware analysis, digital forensics, or threat intelligence
• Experience implementing MLOps pipelines
• Experience deploying AI into production cloud environments

Desired Technical Skills

Artificial Intelligence

• Large Language Models (LLMs)
• Generative AI
• Retrieval-Augmented Generation (RAG)
• Prompt Engineering
• AI Agents
• Agentic AI
• Model Fine-Tuning
• Reinforcement Learning
• Natural Language Processing (NLP)
• Embedding Models

Machine Learning

• TensorFlow
• PyTorch
• Scikit-learn
• XGBoost
• ML Pipelines
• Feature Engineering
• Model Evaluation
• Model Deployment

Cloud

• AWS
• Amazon Bedrock
• SageMaker
• Lambda
• ECS
• EKS
• S3
• IAM
• CloudWatch
• Databricks

Data Engineering

• Spark
• Kafka
• Kinesis
• Airflow
• Prefect
• SQL
• NoSQL
• Data Lakes
• ETL/ELT
• Vector Databases

Software Engineering

• Python
• FastAPI
• REST APIs
• Docker
• Kubernetes
• Git
• GitHub Actions
• Jenkins
• Terraform

Cybersecurity

• Malware Analysis
• Threat Intelligence
• Incident Response
• Digital Forensics
• MITRE ATT&CK
• Detection Engineering
• SIEM Integration
• Security Automation

Desired Certifications

One or more of the following certifications are highly desirable:

• AWS Certified Machine Learning – Specialty
• AWS Certified AI Practitioner
• AWS Solutions Architect – Professional
• Databricks Certified Machine Learning Professional
• Microsoft Azure AI Engineer Associate
• Google Professional Machine Learning Engineer
• CSSLP
• DoD 8140 IAT Level III
• CISSP (Preferred)
• GIAC Certified Forensic Analyst (GCFA) (Preferred)

What Success Looks Like

Within your first year you will:

• Deploy secure AI capabilities supporting DHS cyber operations.
• Develop production-ready LLM and RAG solutions.
• Automate malware analysis and cybersecurity workflows.
• Improve analyst productivity through intelligent automation.
• Establish scalable AI engineering standards and MLOps practices.
• Deliver measurable mission improvements through AI-enabled decision support.

Why Join Argo Cyber?

• Design next-generation AI capabilities supporting national cybersecurity.
• Work with cutting-edge Generative AI, LLMs, and autonomous agent technologies.
• Collaborate with elite cybersecurity engineers, AI researchers, and Federal mission partners.
• Influence AI modernization across critical government missions.
• Competitive compensation, comprehensive benefits, technical training, and opportunities to shape the future of AI-driven cyber operations.

Background & Drug Screening Disclaimer

© Argo Cyber Systems, LLC - All Rights Reserved

Argo Cyber Systems, LLC is committed to maintaining a safe, secure, and trusted workplace for all employees and our federal clients. Employment with Argo Cyber Systems is contingent upon successful completion of all required background investigations and pre-employment screenings , which may include, but are not limited to:

• Criminal background checks (federal, state, and local)
• Employment and education verification
• Reference checks
• Drug screening (in compliance with federal and state law)
• Security clearance verification (as applicable for classified positions)

Candidates selected for employment in positions requiring access to sensitive or classified information may also be subject to additional U.S. Government background investigations and security adjudication processes , including DHS Entry on Duty (EOD) suitability or equivalent federal clearance requirements.

Argo Cyber Systems reserves the right to disqualify or rescind an offer of employment based on the results of any background or screening process that, in the company's judgment, may impact an individual's ability to perform essential job functions or meet contractual obligations.

All background investigations and screenings are conducted in accordance with applicable federal, state, and local laws, including the Fair Credit Reporting Act (FCRA) . Candidates will be notified of their rights and provided an opportunity to review and dispute any adverse findings before final employment determinations are made.

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