ClearGrid is building a debt resolution platform that will leverage machine learning technology to help creditors effectively manage debt. Our mission is to provide a user-friendly, transparent, and personalized debt recovery experience that prioritizes the financial well-being of borrowers and lenders.

We are looking for a capable VP of Engineering to join our growing team As the VP of Engineering,you will define and execute ClearGrid’s technology vision, leading the build of a highly secure, scalable debt resolution platform trusted by major banks and lenders across the region. You will drive innovation in reasoning models, applied machine learning, data engineering, and automation to transform how debt is resolved while ensuring compliance with financial regulations and safeguarding sensitive data.

You will also be responsible for leading the technology strategy and development efforts of the company. Your experience in other fast-growing technology companies will help you build the best products and systems for the organization while taking responsibility for growing the engineering team.

This role requires strong leadership and technical skills as well as the ability to get things done fast with exceptional results.

Responsibilities:

• Develop and implement the technology strategy in alignment with the company's goals and objectives.

• Build and manage the technology team to deliver quality software products and services.

• Lead the design, development, and implementation of the company's software products and services.

• Ensure the scalability, reliability, and security of the company's technology platform.

• Drive the design and productionization of reasoning models and ML systems for:

  • Borrower behavior prediction (likelihood to repay, roll rates, default risk).

  • Personalized repayment plan recommendations.

  • AI-driven customer communication (voice/text agents for negotiation and support).
    Early warning and fraud/skip-tracing signals.

• Oversee ML lifecycle management (data pipelines, feature engineering, experimentation, deployment, monitoring, model drift management).

• Leverage LLMs for conversational agents, reasoning tasks, and borrower support automation, ensuring safe and compliant deployment in production.

• Identify and evaluate emerging technologies and market trends to keep the company at the forefront of innovation.

• Collaborate with other senior leaders to ensure the technology solutions align with business needs and requirements.

• Manage and lead the development of large-scale platforms with a significant amount of data.

• Design and implement microservices and serverless architectures.

• Implement and maintain robust security protocols and practices across the technology stack, including network security, data security, and user authentication.

• Monitor and mitigate potential security threats and vulnerabilities, ensuring that the company's data and systems are protected at all times.

• Keep up-to-date with the latest developments in security technologies and best practices and ensure the company's security protocols are up-to-date.

Requirements:

• Bachelor's in Computer Science, Engineering, or related field. Master’s Degree preferred.

• Proven experience in an engineering leadership role in a technology startup or high-growth company.

• Strong technical knowledge and experience in machine learning, AI, data science, and software engineering.

• Deep technical expertise in reasoning models and machine learning with a track record of building and deploying ML systems in production at scale.

• Hands-on experience with ML frameworks (e.g., TensorFlow, PyTorch) and MLOps tooling (e.g., MLflow, Kubeflow, SageMaker).

• Experience with deploying and scaling LLMs (e.g., OpenAI, Anthropic, LLaMA, or similar), including fine-tuning, prompt design, and integration into production systems.

• Experience in managing, leading, and scaling software development teams across multiple locations.

• Strong strategic thinking and problem-solving skills.

• Excellent communication and leadership skills.

• Familiarity with microservices and serverless architectures.

• Experience with Java, Python, or other modern programming languages.

• Experience implementing and maintaining robust security protocols and practices across the technology stack.

• Experience managing platforms with large amounts of sensitive data.