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

Node.Digital

Herndon (VA)

Hybrid

USD 140,000 - 190,000

Full time

4 days ago

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Benefits offered by this job

Medical

Dental

Vision

401K Matching

3 weeks PTO/Sick

11 Paid Holidays

Pre-Approved Online Training

Job summary

Node.Digital is seeking an Intelligent Automation/AI-ML Engineer (Full Stack) in Herndon, VA, with 8+ years of experience. You will architect intelligent applications that embed AI/ML, build end-to-end solutions, and standardize model governance and deployment.

Responsibilities include designing scalable AI-enabled workflows, ensuring data integrity, and collaborating with IT and data teams to deliver enterprise-grade applications.

Qualifications

Bachelor's degree in CS, Data Science, Engineering, or related field or equivalent experience.
Hands-on intelligent application development experience.
Experience with open source AI models and document understanding techniques.
Proficiency in Python and ML libraries (scikit-learn, pandas, TensorFlow or PyTorch).
Understanding of ML lifecycle: data prep, training, evaluation, deployment, monitoring, retraining.
Experience building document processing and data cleansing solutions.
Strong troubleshooting and production-support skills.
APIs, integrations, SQL, and data formats (JSON/XML/CSV).
Full stack development: Python/Java backend and Angular frontend.

Responsibilities

Design, build, and deploy intelligent application solutions integrating AI/ML models with workflows.
Create reusable components for document processing, data extraction, classification, and cleansing.
Build end-to-end applications as a full stack engineer (UI, APIs, models, databases, business rules).
Expose AI capabilities via MCP servers for consistent reuse across apps.
Implement governance, testing, and auditability for AI-enabled decisions.
Manage lifecycle of open source models including deployment and retraining.
Monitor model performance, drift, and optimize to maintain efficiency.
Troubleshoot post-implementation issues in ML pipelines and apps.
Collaborate with analysts, data teams, and IT to align with business goals.

Skills

Python

Java backend

Angular frontend

APIs

ML libraries (TensorFlow/PyTorch)

SQL/NoSQL

Problem solving

Education

Bachelor's degree in Computer Science or related field

Tools

MCP (Model Context Protocol)

Open-source AI models

TensorFlow/PyTorch

Job 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.

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.