Model Risk AI Governance

About Us:

Solytics Partners is a Global Analytics firm, recognized with multiple industry awards for innovation and excellence. Our team comprises experts with deep domain knowledge in risk, analytics, AI/ML, AML/FCC, and fraud. By converging this expertise with cutting-edge technologies like AI, Machine Learning, Generative AI, and Large Language Models (LLMs), we deliver powerful automated platforms and incisive point solutions.

Our offerings enable clients to streamline and future-proof their risk, AML, and analytics processes, comply seamlessly with global regulations, and safeguard financial systems. Whether its solving complex challenges or driving operational efficiency, Solytics Partners is committed to empowering organizations with transformative tools to stay ahead in an evolving regulatory landscape.

Job Summary:

We are seeking Model Risk AI Governance Engineer to support the governance, oversight, and lifecycle management of Artificial Intelligence (AI) and Machine Learning (ML) solutions within a highly regulated environment. This role combines technical expertise in AI/ML with governance and risk management responsibilities. The successful candidate will work closely with data scientists, AI engineers, business stakeholders, and risk teams to ensure AI solutions are appropriately governed, monitored, documented, and aligned with organizational policies and regulatory expectations. The position offers an opportunity to contribute to the development of responsible AI practices while supporting the implementation of scalable governance processes across the AI ecosystem.

Key Responsibilities:

AI Governance & Lifecycle Oversight

• Support the implementation and continuous improvement of AI governance frameworks and control processes.
• Facilitate governance reviews, approval workflows, and control checkpoints throughout the AI/ML lifecycle.
• Assist in conducting risk assessments for AI and machine learning use cases, ensuring risks are identified, documented, and appropriately mitigated.
• Promote adherence to internal governance standards, policies, and regulatory requirements.

AI Inventory & Model Management

• Maintain and enhance centralized repositories used to track AI models and AI-enabled solutions.
• Ensure AI assets are accurately documented, classified, and managed throughout their lifecycle.
• Support the onboarding of new AI initiatives using established materiality, criticality, and risk-based assessment frameworks.
• Track model and AI solution status across development, validation, deployment, monitoring, and retirement stages.

Technical Controls & Engineering Support

• Collaborate with AI/ML engineering teams to ensure governance and risk requirements are incorporated into development processes.
• Support implementation of monitoring, logging, explainability, and model performance controls.
• Develop and enhance automation solutions for governance workflows, inventory management, and reporting activities using Python or similar technologies.
• Assist in establishing data lineage, traceability, and auditability across AI systems and supporting infrastructure.

Monitoring, Reporting & Risk Analytics

• Create and maintain dashboards and reporting solutions that provide visibility into AI inventory, governance activities, and risk metrics.
• Monitor key indicators such as model performance, drift, fairness, explainability, and operational risks.
• Support preparation of management and governance committee reports.
• Identify control gaps, track remediation activities, and contribute to ongoing risk management initiatives.

Stakeholder Collaboration

• Partner with business, technology, data science, compliance, validation, and audit teams to support effective AI governance practices.
• Assist in awareness and training initiatives related to responsible AI, governance standards, and lifecycle management requirements.
• Support internal reviews and regulatory engagements relating to AI risk and governance processes.

Key Requirements

Education

• Bachelors or masters degree in computer science, Data Science, Artificial Intelligence, Engineering, Mathematics, Statistics, or a related quantitative discipline.

Experience

• 5+ years of experience in AI engineering, machine learning, data science, model governance, model risk management, or related disciplines.
• Experience supporting AI/ML lifecycle management, governance frameworks, or risk oversight activities.
• Exposure to model inventories, metadata management, model documentation, or governance processes is highly desirable.
• Experience working within regulated industries such as banking, financial services, insurance, or healthcare is advantageous.

Technical Skills

• Strong programming skills in Python and experience developing automation solutions.
• Solid understanding of machine learning concepts, model development processes, evaluation techniques, and monitoring practices.
• Familiarity with model governance, AI risk management, or responsible AI frameworks.
• Understanding of data governance principles, including lineage, traceability, and documentation.
• Experience with reporting and visualization tools such as Power BI or Tableau.
• Knowledge of model monitoring, explainability, fairness, and model risk concepts is preferred.