AI Engineer

Description:
We are seeking an AI Engineer to support the deployment and integration of advanced AI features into enterprise and cloud-based environments. This role will focus on operationalizing machine learning models, ensuring secure and scalable implementations, and supporting government-compliant solutions. The ideal candidate has hands-on experience with AWS-native AI services, testing frameworks, and cloud automation practices.

The ideal candidate will have hands-on experience with AWS AI/ML services, test automation, and secure cloud deployments, particularly within FedRAMP-compliant environments. A collaborative mindset and a passion for delivering scalable, high-quality solutions are essential.

Location: Fully Remote

Pay Rate: 60-63hr. W2

This is a contract-to-hire opportunity. Applicants must be willing and able to work on a W2 basis and convert to FTE following contract duration. For our W2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.

Responsibilities: Key Responsibilities

AI Feature Implementation Support

• Deploy AI/ML models into production using AWS services (SageMaker, Bedrock, Lambda, Comprehend).
• Collaborate with data scientists and engineers to scale prototypes into enterprise-ready components.
• Develop AI features such as predictive analytics, anomaly detection, recommendation engines, and natural language interfaces.
• Ensure compliance with performance, security, and FedRAMP requirements.

Testing and Validation

• Create and execute test plans for AI models, including unit, integration, regression, and performance testing.
• Build automated test frameworks to validate accuracy and reliability.
• Monitor AI feature behavior in staging and production, resolving issues proactively.
• Document test results, bug reports, and performance metrics.

Cloud Integration and Automation

• Integrate AI features into enterprise workflows, APIs, and data pipelines using AWS-native tools.
• Implement CI/CD pipelines and Infrastructure-as-Code (IaC) for deployment and testing.
• Manage version control and configuration for AI-integrated components.

Experience Requirements: Required Qualifications

• 2+ years of experience in AI/ML engineering with hands-on deployment and system integration.
• Proficiency in Python and ML libraries (scikit-learn, TensorFlow, PyTorch).
• Experience with AWS AI/ML services (SageMaker, Comprehend, Rekognition, Bedrock).
• Familiarity with REST APIs, microservices, and enterprise integrations.
• Experience with test automation tools (PyTest, Selenium, JUnit).
• General experience with Java for backend/integration tasks.
• Understanding of FedRAMP compliance and secure cloud deployment practices.

Preferred Qualifications

• Experience with DevOps practices and CI/CD pipelines for AI/ML applications.
• Familiarity with containerization/orchestration (Docker, Kubernetes, ECS/EKS).
• Knowledge of government contracting environments, compliance, and audit standards.
• Strong communication, problem-solving, and documentation skills.

Education Requirements: Education

• Bachelor's degree is a nice to have.