About the Role
This role sits at the intersection of AI engineering, platform operations, and governance. As an AI Platform Developer, you will help shape and sustain enterprise AI capabilities by supporting the systems, processes, and controls that enable models to be developed, deployed, monitored, and managed effectively across their lifecycle while working closely with technical and business stakeholders.
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Responsibilities
- Administer, configure, maintain, and enhance the enterprise AI Governance Platform.
- Develop, integrate, deploy, and operationalize AI models and solutions spanning machine learning, deep learning, generative AI, and agentic AI.
- Manage model onboarding, updates, reassessments, and retirement.
- Customize platform workflows, forms, assessment templates, dashboards, and reports.
- Support model development, testing, validation, deployment, and monitoring across development, testing, and production environments.
- Troubleshoot platform incidents, integrations, configuration defects, and model-performance issues.
- Monitor model performance, drift, availability, and quality.
- Maintain technical documentation, operational procedures, and knowledge-transfer materials.
- Support Responsible AI, model-risk controls, data privacy, and data-governance requirements.
- Collaborate with AI engineers, governance specialists, and client stakeholders on platform enhancements.
Requirements
- Bachelor’s or Master’s degree in Artificial Intelligence or a related field.
- 6+ years of professional experience in AI engineering, including AI model development, machine-learning implementation, model integration, evaluation, monitoring, and operationalization.
- 3+ years of hands-on experience with an enterprise AI Governance Platform, including model onboarding, workflow configuration, assessments, monitoring, or reporting.
- Hands-on experience with Python, generative AI, and agentic AI.
- Strong experience with APIs and integrations, MLOps, model deployment, and model lifecycle management in production operations.
- Hands-on experience with model monitoring, performance monitoring, model drift analysis, validation, and troubleshooting.
- Experience applying Responsible AI, Model Risk Management, Data Privacy, and Data Governance in AI environments.
- Experience collaborating directly with client stakeholders, AI engineers, and governance specialists to support AI platform operations, governance reviews, troubleshooting, or platform enhancements.
- Able to work on-site.
- Hands-on experience with TensorFlow, PyTorch, or Scikit-learn is a plus.
- Direct enterprise client-facing experience, including leading client presentations or governance discussions, is a plus.
Benefits
- Private Health Insurance
- Training & Development
