Agile Programming Methodologies, Algorithms, Amazon Web Services (AWS), Artificial Intelligence (AI), Automation, Background Investigation, Cloud Computing, Computer Science, Continuous Deployment/Delivery, Continuous Integration, Data Quality, Data Science, Data Sets, Deep Learning, DevOps, Federal Government, GCP (Good Clinical Practices), Government, Machine Learning, Microsoft Windows Azure, Predictive Modeling, Prototyping, Technical Writing, Theater Production, Training Data Sets, United States Citizen, Work From Home
Job Summary::
The Low Code AI Engineer will support the International Trade Administration (ITA) AI Center of Excellence (AI‑CoE) by developing, deploying, and maintaining scalable artificial intelligence and machine learning solutions. This role focuses on building predictive models, automating ML pipelines, and operationalizing AI solutions using low‑code and cloud‑based platforms within a federal environment.
*This position is contingent upon contract award.*
Job Duties and 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 versioning, deployment, and lifecycle of models and datasets.
- Ensure data quality, accuracy, and integrity throughout the ML lifecycle.
- Serve and scale ML models in cloud environments.
- Deploy, monitor, and maintain AI/ML solutions in development, staging, and production.
- Collaborate with cross‑functional teams using SAFe Agile methodologies.
- Utilize Government‑provided DevOps and cloud platforms.
- Produce clear technical documentation compliant with federal standards.
- Other duties as assigned.
Job Requirements (Education/Skills/Experience)::
- U.S. Citizenship (required). MUST have a NACI or higher background investigation.
- Minimum two (2) years of experience.
- Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field (or equivalent experience).
- Experience developing and deploying machine learning models.
- Hands‑on experience with data preprocessing, feature engineering, and model evaluation.
- Familiarity with ML pipeline automation and orchestration tools.
- Experience working in Agile or SAFe environments.
Desired Qualifications:
- Master’s degree in a related technical field.
- Experience with low‑code or no‑code AI/ML platforms.
- Experience deploying models in cloud environments (AWS, Azure, or GCP).
- Knowledge of MLOps practices, CI/CD pipelines, and monitoring tools.
- Prior experience supporting federal or government clients.
- Familiarity with AI governance, ethics, and security considerations.
- Experience using Azure DevOps or similar tools.
Work Location: Remote work preferred with occasional on‑site support in Washington, DC, as required.
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 their 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. We participate in E-Verify.
D
Dine Development Corporation
DDC is a tribally-owned holding corporation that was established in 2004 to provide viable economic opportunities for the Navajo Nation. Headquartered in Window Rock, AZ, we are committed to preserving our rich culture through a continual focus on core values. Through strategic growth, we have dynamically expanded our family of companies while supporting the Navajo Nation.
Our subsidiaries provide professional and technical IT and environmental services to a broad portfolio of commercial, tribal, and federal clients.
100 to 499 employees
401K, Employee Referral Program, Tuition Reimbursement, Life Insurance