The Low Code AI Engineer will support the International Trade Administration (ITA) Artificial Intelligence Center of Excellence (AI‑CoE) by designing, developing, deploying, and maintaining scalable artificial intelligence and machine learning solutions. This role emphasizes the use of low‑code and cloud‑based platforms to operationalize AI capabilities within a secure federal environment. The ideal candidate will have hands‑on experience building predictive models, automating ML pipelines, and supporting AI solutions across the full lifecycle in an Agile/SAFe delivery environment.
*This position is contingent upon contract award.*
Responsibilities
- Develop algorithms and predictive models using machine learning and deep learning frameworks.
- Scale AI/ML prototypes into production‑ready solutions.
- Preprocess, validate, and manage structured and unstructured datasets.
- Automate, orchestrate, and monitor machine learning pipelines.
- Manage model and dataset versioning, deployment, and lifecycle management.
- Ensure data quality, accuracy, and integrity throughout the ML lifecycle.
- Serve and scale machine learning models in cloud environments.
- Deploy, monitor, and maintain AI/ML solutions across development, staging, and production environments.
- Collaborate with cross‑functional teams using SAFe Agile methodologies.
- Utilize Government‑provided DevOps and cloud platforms to support AI/ML initiatives.
- Produce clear, accurate technical documentation compliant with federal standards and policies.
- Performs other related duties as assigned.
Qualifications
- U.S. Citizenship is required.
- Must possess a NACI or higher background investigation.
- Minimum of two (2) years of relevant professional experience.
- Bachelor’s degree in Computer Science, Data Science, Engineering, or a related technical field, or equivalent experience.
- Experience developing, evaluating, and deploying machine learning models.
- Hands‑on experience with data preprocessing, feature engineering, and model performance evaluation.
- Familiarity with machine learning pipeline automation and orchestration tools.
- Experience working in Agile or SAFe development environments.
Desired Qualifications
- Master’s degree in Computer Science, Data Science, Engineering, or a related technical field.
- Experience with low‑code or no‑code AI/ML platforms.
- Experience deploying AI/ML models in cloud environments such as AWS, Azure, or Google Cloud Platform.
- Knowledge of MLOps practices, CI/CD pipelines, model monitoring, and lifecycle management tools.
- Prior experience supporting federal or government clients.
- Familiarity with AI governance, ethics, security, and compliance considerations.
- Experience using Azure DevOps or similar DevOps tools.
Work Location
Remote work is preferred, with occasional on‑site support in Washington, DC, as required.
About Us
Diné Development Corporation (DDC) is a Navajo Nation owned family of companies that provides government agencies and commercial organizations with high‑quality IT, professional, environmental, and research and development services. DDC is dedicated to empowering the Navajo Nation and the communities we serve.
Benefits
Eligible full‑time employees receive a comprehensive benefits package, including medical, dental, vision, life and disability coverage, retirement savings with company match, paid time off, voluntary supplemental benefits, and access to an employee assistance program. The package also includes educational assistance, with tuition reimbursement.
Equal Employment Opportunity
This contractor and subcontractor shall abide by the requirements of 41 CFR 60‑1.4(a), 60‑300.5(a), and 60‑741.5(a). These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on race, color, religion, sex, sexual orientation, gender identity, national origin, or for inquiring about, discussing, or disclosing information about compensation, or any other basis prohibited by law.
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