Node.Digital

Develops AI-driven digital solutions for missions

Intelligent Automation/AI-ML Engineer - Full Stack Engineer

AI Application Engineering +1Confirmed live in the last 24 hours

Full-timeHerndon, VA, USA

About the Job

Requirements

A bachelor's degree in Computer Science, Data Science, Engineering, Information Systems, or a related field, or equivalent experience.
Experience developing intelligent applications and building enterprise applications hands-on.
Working experience with open-source AI models and document-understanding techniques, or comparable AI/ML frameworks and tools.
Proficiency in Python and common machine-learning libraries such as scikit-learn, pandas, TensorFlow, or PyTorch.
Understanding of the machine-learning lifecycle, including data preparation, training, evaluation, deployment, monitoring, and retraining.
Experience building document-processing and data-cleansing solutions.
Strong troubleshooting and problem-solving skills in production environments.
Knowledge of APIs, integrations, SQL, and data formats such as JSON, XML, and CSV.
Excellent written and verbal communication skills.
Full-stack development experience, including Python and Java for backend services and APIs, and Angular for front-end user interfaces.
Hands-on experience with Model Context Protocol (MCP), including building or integrating MCP servers and tools.
Experience designing and working with relational and/or NoSQL databases, including schema design and query optimization.
U.S. citizenship is required for project eligibility and security-clearance requirements.

Responsibilities

Design, build, and deploy intelligent application solutions that integrate AI/ML models with business workflows using modern development frameworks and open-source AI models.
Develop repeatable, reusable components and services for document processing, data extraction, classification, and data cleansing.
Translate business requirements into technical designs, solution architectures, and documented standards.
Build end-to-end full-stack applications, including front-end user interfaces, backend servers and APIs, AI/ML models, databases, and business rules.
Develop and expose AI capabilities and tools through MCP servers so applications can use them consistently and repeatedly.
Implement business rules and decision logic alongside AI models, with governance, testing, and auditability.
Manage the lifecycle of open-source AI models, including deployment, versioning, monitoring, retraining, and retirement.
Monitor model performance, accuracy, and drift, and tune solutions to maintain operational efficiency.
Implement feedback loops, including human-in-the-loop validation, to drive continuous learning and refinement.
Optimize application performance, scalability, and resource utilization.
Troubleshoot and resolve post-implementation issues in open-source AI models, ML pipelines, and integrated applications.
Perform root-cause analysis on production incidents and implement lasting fixes.
Maintain runbooks, support documentation, and knowledge-base articles.
Partner with infrastructure, security, and platform teams to maintain a stable and compliant environment.
Work with business analysts, process owners, data teams, and IT to deliver solutions aligned with business goals.
Communicate progress, risks, and results to technical and non-technical audiences.

Desired Qualifications

Cloud, AI/ML, or software-development certifications, such as advanced developer or solution architect credentials.
Experience with OCR, NLP, computer vision, or generative AI/LLM integration.
Familiarity with Azure, AWS, or GCP and MLOps practices.
Knowledge of Agile delivery, CI/CD, and source control such as Git.
Understanding of data governance, security, and responsible AI practices.

Intelligent Automation/AI-ML Engineer (Full Stack Engineer)

Node.Digital · Herndon, United States (Hybrid) · Full-time · Posted 2026-10-28

Workplace: hybrid

Department: EPIC - DHS

Description

Intelligent Automation/AI-ML Engineer (Full Stack Engineer)

Location: Herndon, VA (Hybrid Work)

This position supports a U.S. Federal Government project. U.S. citizenship is required to meet the project’s eligibility and security clearance requirements.

Experience: 8+ yrs

Position Summary

The Intelligent Application / AI-ML Engineer is the architect and guardian of intelligent application solutions that incorporate AI/ML technologies using tools such as open source AI models. This role ensures the operational efficiency and continuous refinement of integrated AI/ML solutions across the organization. Responsibilities span the design, maintenance, and optimization of intelligent applications, including troubleshooting and resolving issues that arise after implementation.

The engineer will also explore new ways to embed artificial intelligence and machine learning into applications, supporting continuous improvement, learning, and augmented decision making. A key focus is building repeatable, reusable intelligent solutions for document processing, data cleansing, and similar use cases.

Key Responsibilities

Solution Design and Development

Design, build, and deploy intelligent application solutions that integrate AI/ML models with business workflows using modern development frameworks and open source AI models.
Develop repeatable, reusable components and services for document processing, data extraction, classification, and data cleansing.
Translate business requirements into technical designs, solution architectures, and documented standards.
Build end-to-end applications as a full stack engineer, including front-end user interfaces, backend servers and APIs, AI/ML models, databases, and business rules.
Develop and expose AI capabilities and tools through Model Context Protocol (MCP) servers so applications can use them in a consistent, reusable way.
Implement business rules and decision logic that work alongside AI models, with clear governance, testing, and auditability.

AI/ML Operations and Optimization

Manage the lifecycle of open source AI models, including deployment, versioning, monitoring, retraining, and retirement.
Monitor model performance, accuracy, and drift, and tune solutions to maintain operational efficiency over time.
Implement feedback loops (e.g., human-in-the-loop validation) to drive continuous learning and refinement.
Optimize application performance, scalability, and resource utilization.

Support and Troubleshooting

Troubleshoot and resolve post-implementation issues in open source AI models, ML pipelines, and integrated applications.
Perform root cause analysis on production incidents and implement lasting fixes.
Maintain runbooks, support documentation, and knowledge base articles.
Partner with infrastructure, security, and platform teams to maintain a stable and compliant environment.

Collaboration

Work with business analysts, process owners, data teams, and IT to deliver solutions aligned with business goals.
Communicate progress, risks, and results clearly to technical and non-technical audiences.

Requirements

Required Qualifications

Bachelor's degree in Computer Science, Data Science, Engineering, Information Systems, or a related field (or equivalent experience).
Experience in intelligent application development, with hands-on experience building enterprise applications.
Working experience with open source AI models and document understanding techniques, or comparable AI/ML frameworks and tools.
Proficiency in Python and common ML libraries (e.g., scikit-learn, pandas, TensorFlow or PyTorch).
Understanding of the ML lifecycle: data preparation, training, evaluation, deployment, monitoring, and retraining.
Experience building document processing and data cleansing solutions.
Strong troubleshooting and problem-solving skills in production environments.
Solid knowledge of APIs, integrations, SQL, and data formats (JSON, XML, CSV).
Excellent written and verbal communication skills.
Full stack development experience: proficiency in Python and Java for backend services and APIs, and Angular for front-end user interfaces.
Hands-on experience with Model Context Protocol (MCP), including building or integrating MCP servers and tools.
Experience designing and working with relational and/or NoSQL databases, including schema design and query optimization.

Preferred Qualifications

Cloud, AI/ML, or software development certifications (e.g., advanced developer or solution architect credentials).
Experience with OCR, NLP, computer vision, or generative AI/LLM integration.
Familiarity with cloud platforms (Azure, AWS, or GCP) and MLOps practices.
Knowledge of Agile delivery, CI/CD, and source control (e.g., Git).
Understanding of data governance, security, and responsible AI practices.

Benefits

Medical
Dental
Vision
Basic Life
Health Saving Account
401K Matching
Three weeks of PTO/Sick
11 Paid Holidays
Pre-Approved Online Training

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About the Company

Node.Digital

Develops AI-driven digital solutions for missions

Node.Digital builds digital solutions using AI automation and machine learning to help clients achieve their missions. Its approach centers on designing and deploying AI-powered software that automates processes, analyzes data, and supports decision-making for complex, mission-focused problems. Unlike general software firms, Node.Digital emphasizes delivering tailored, mission-driven solutions that address each customer’s unique objectives. The company’s goal is to enable organizations to operate more effectively and achieve impactful outcomes by applying AI and ML to real-world challenges.

Company size: 11-50
Company stage: Not listed
Total funding: Not listed
Headquarters: Herndon, VA
Founded: 2017

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