Hybrid AI Software Engineer

at Control Risks

• Job title: AI Software Engineer
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Azure, Cloud, Java, Python, PyTorch, Scikit-Learn, Tensorflow
• Location requirements: Hybrid, Panama City, Panama

About the role

• AI Software Engineer designing, developing, and deploying AI technology solutions. Collaborating with teams to build scalable AI systems and optimizing models for production use.

Responsibilities

• Design, develop, and maintain AI and machine learning models and applications.
• Translate business problems into effective AI solutions.
• Collaborate with data scientists, engineers, and stakeholders to deliver production-ready AI systems.
• Implement, test, and optimize machine learning algorithms and pipelines.
• Deploy, monitor, and maintain AI models in production environments (using MLOps best practices).
• Analyze large datasets to extract insights and improve model performance.
• Document AI development processes and communicate complex concepts to non-technical stakeholders.
• Stay up to date with the latest AI research, frameworks, and industry trends.
• Ensure ethical, legal, and societal considerations are addressed in AI solutions.
• Troubleshoot and resolve issues related to AI systems and data pipelines.

Requirements

• Strong programming skills in Python (and optionally C#, Java, R, or C++).
• Experience with machine learning and deep learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Proficiency in designing, training, and deploying AI/ML models.
• Experience with cloud-based AI platforms (e.g., Azure ML, AWS SageMaker, Google Vertex AI).
• Familiarity with MLOps tools and practices (e.g., MLflow, CI/CD for ML).
• Understanding of data engineering, data preprocessing, and feature engineering.
• Experience with REST APIs and integrating AI models into software products.
• Strong knowledge of statistics, algorithms, and data structures.
• Excellent command of the English language.
• Experience with NLP, computer vision, or generative AI (LLMs, RAG, etc.).
• Familiarity with Azure DevOps, Azure API Manager, Cosmos DB, and related Microsoft technologies.
• Exposure to ethical AI, bias mitigation, and responsible AI practices.
• Experience with version control, containerization, and cloud deployment.
• A strong academic background including a degree in a relevant field.