AI/ML Automation Engineer at Argo Cyber Systems in Arlington, VA, USA

Job description

• 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.
• 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.

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.

Requirements

• 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
• 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
• 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
• Detection Engineering
• SIEM Integration
• Security Automation
• 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
• GIAC Certified Forensic Analyst (GCFA) (Preferred)

Skills

Required

• Python
• Databricks AI Platform
• Machine learning pipelines
• Large Language Models (LLMs)
• Amazon Bedrock
• AWS AI services
• REST APIs
• Cloud-native applications
• Git
• CI/CD pipelines
• Software development best practices

Preferred

• Generative AI
• Autonomous AI agents
• RAG architectures
• LangChain
• LangGraph
• CrewAI
• AutoGen
• Semantic Kernel

Benefits

• 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.