Senior Data and AI Platform Engineer

Job Summary:

The Senior Data and AI Platform Engineer designs, develops, and maintains the College's enterprise data and AI platform. The position integrates institutional systems, develops governed data pipelines, data models, and analytics, creates secure APIs and Model Context Protocol (MCP) services, and implements governed AI-supported applications and workflows. Initial efforts will focus on institutional analytics, with the platform designed to expand into operational, administrative, academic, security, and student success initiatives across the College.

Supervisory Responsibilities:

None.

Physical Requirements:

Prolonged periods of sitting at a desk and working on a computer.

Personal Qualities:

Demonstrates Christian character, integrity, humility, and a commitment to fostering a Christ-centered professional environment.

Demonstrates a spirit of cooperation, servant leadership, and a willingness to support colleagues, students, and the broader College community.

Demonstrates intellectual curiosity and a commitment to continuous learning, particularly in emerging technologies, analytics, and artificial intelligence.

Exercises sound judgment, discretion, and ethical decision-making when handling sensitive institutional data and evaluating technology solutions.

Demonstrates the ability to translate complex technical concepts into practical solutions that support the College's mission and strategic objectives.

Demonstrates the desire and ability to disciple, mentor, and positively influence students.

Conducts oneself in a manner consistent with the mission, values, and Statement of Faith of Lancaster Bible College.

Education and Experience:

Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, Information Technology, or a related field, or five years of progressively responsible experience in software development, enterprise systems integration, or data engineering, with demonstrated experience designing and implementing AI-enabled solutions. Equivalent combinations of education and experience may be considered.

Experience in higher education preferred.

Industry-recognized certifications in relevant technical disciplines are preferred, with a demonstrated commitment to continuous professional development in emerging data and AI technologies.

Required Skills/Abilities:

Experience integrating APIs, databases, and enterprise systems.

Strong Python development skills and proficiency with SQL, relational data, and analytical query logic.

Git and modern software development practices.

Practical experience using modern software development environments and AI-assisted coding tools (such as Visual Studio Code with AI extensions or comparable platforms).REST, JSON, authentication, pagination, and error handling.

Testing, debugging, logging, and documentation.

Familiarity with cloud data platforms, analytical databases, data pipelines, and ELT or ETL practices.

Ability to design and develop services, tools, or internal applications.

Strong systems thinking and investigative problem-solving skills, including the ability to translate institutional needs and operational procedures into technical requirements, data models, system integrations, and secure, governed AI-supported workflows.

Strong understanding of information security, privacy, least privilege, service identities, credential management, access controls, and the responsible handling of institutional data.

Ability to communicate complex technical concepts, findings, assumptions, risks, and recommendations clearly to technical and nontechnical audiences.

Duties/Responsibilities:

Design, build, maintain, and document the College’s enterprise data and AI platform, including its architecture, development standards, deployment processes, and operational procedures.

Develop and support integrations among enterprise applications, databases, APIs, cloud services, analytical platforms, and AI tools.

Build and maintain Model Context Protocol (MCP) servers and other structured interfaces that allow AI systems to safely access, query, and reason over institutional data and systems.

Establish and maintain the institutional data warehouse and related technologies, enabling secure and governed access to institutional data for analytics, enterprise applications, and AI through Model Context Protocol (MCP) and other structured interfaces.

Develop automated testing, reconciliation, logging, and monitoring processes to verify data quality, integration reliability,…