AI/ML Automation Engineer

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 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.

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

TensorFlow

PyTorch

Scikit-learn

XGBoost

ML Pipelines

Feature Engineering

Model Evaluation

Model Deployment

AWS

Amazon Bedrock

SageMaker

Lambda

ECS

EKS

S3

IAM

CloudWatch

Databricks

Spark

Kafka

Kinesis

Airflow

Prefect

SQL

NoSQL

Data Lakes

ETL/ELT

Vector Databases

Python

FastAPI

REST APIs

Docker

Kubernetes

Git

GitHub Actions

Jenkins

Terraform

Malware Analysis

Threat Intelligence

Incident Response

Digital Forensics

MITRE ATT&CK

Detection Engineering

SIEM Integration

Security Automation

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)

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.

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.

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.