AI Engineer (Machine Learning/Cloud Infrastructure)

Responsibilities

AI Infrastructure & Environment Management

• Manage and maintain cloud environments for AI workloads
• Ensure secure and stable connectivity between enterprise systems and AI platforms
• Monitor system performance and maintain reliability of AI models in production
• Implement security controls for AI data handling and model deployment

AI Prototyping & Technical Evaluation

• Conduct technical evaluation of AI tools, frameworks, and vendor solutions
• Build proof-of-concepts to validate AI feasibility and performance
• Stress-test AI APIs, model endpoints, and third-party integrations
• Document findings and provide recommendations on AI adoption

Data Pipelines & MLOps Engineering

• Develop and maintain data pipelines for AI training and inference
• Implement MLOps practices for model deployment, monitoring, and lifecycle management
• Build and maintain model serving infrastructure and APIs
• Ensure reliable data flow between source systems and AI model

Requirements

• Degree in Computer Science, Data Science, AI/ML, or related field
• 3+ years of experience in AI/ML engineering or related technical roles
• Strong Python programming skills with ML libraries (TensorFlow, PyTorch, scikit-learn)
• Experience with cloud platforms (AWS, Azure, or GCP)
• Knowledge of MLOps, model deployment, and monitoring
• Experience with API development and integration for AI services
• Understanding of data pipelines and ETL processes
• Familiarity with government technology standards and AI governance frameworks
• Experience with Government Commercial Cloud (GCC) or similar secure environments