Business Systems AI Engineer

The Business Systems AI Engineer serves as a key technical contributor responsible for designing, implementing, and maintaining intelligent, automated, and scalable solutions across Mercury’s business systems. This role integrates advanced application engineering with modern AI capabilities to enhance efficiency, data accessibility, and decision-making across the organization. The engineer will partner closely with business stakeholders, platform owners, and cross-functional teams to deliver secure, compliant, and forward‑looking solutions that align with Mercury’s digital transformation and AI adoption strategy.

Primary Responsibilities

AI‑Enabled System Engineering

• Design, develop, and operationalize AI-driven features, including predictive analytics, intelligent workflow automation, and NLP-based process enhancements.
• Build and manage enterprise-grade automation pipelines to reduce manual effort and improve system reliability.

Platform Development & Integration

• Engineer scalable integrations between core systems such as Oracle, Salesforce, Foundry, and low‑code platforms, ensuring efficient and secure data interchange.
• Develop and maintain application logic, transformation code, and reusable components supporting Business Systems workflows.

Automation & Analytics

• Implement advanced analytics, dashboards, and insights leveraging AI, machine learning, and automation frameworks.
• Support data governance, lineage tracking, and compliance requirements across integrated enterprise platforms.

Technical Leadership & Governance

• Contribute to architectural design discussions, system standards, and long‑term platform strategy.
• Ensure solutions adhere to Mercury’s AI governance policies, cybersecurity requirements, and data protection standards.
• Produce documentation, training materials, and operational procedures consistent with established Business Systems practices.

Required Qualifications

• Bachelor’s degree in Information Systems, Computer Science, Engineering, or equivalent experience.
• 4–7 years of experience in application engineering, enterprise systems integration, or custom application development.
• Hands-on experience with AI‑enabled tools, automation frameworks, and modern integration technologies.
• Strong proficiency in Python, SQL, or similar languages used for automation and data processing.
• Ability to translate business requirements into scalable technical solutions with measurable impact.

Preferred Qualifications

• Experience designing AI-driven workflows or developing predictive models.
• Experience with low-code tools such as Mendix
• Familiarity with Foundry, Power Platform, Salesforce, or Oracle Fusion integration patterns.
• Knowledge of enterprise AI governance, data protection controls, or secure model deployment.
• Certifications in cloud, AI, or platform engineering (PL‑300, Power Platform, AWS/Azure AI specialties).