AI Platform Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and manage the next generation of AI infrastructure at GiveCampus.

• Construct a shared context and memory for the company and partners to be utilized across agents.

• Establish identity management, access controls, audit permissions, credential oversight, and MCP connection management.

• Create a comprehensive registry of current AI tools and systems.

• Implement governance measures, including production evaluation gates, audit trails, monitoring systems, prompt-injection safeguards, and data leak prevention strategies.

• Make informed build-versus-buy decisions regarding Infrastructure.

• Develop templates and guidelines for Taskforce builders.

• Assess the impact of AI initiatives by department.

• Create agents capable of executing end-to-end processes and enhancing agent autonomy over time.

• Develop an internal deployment platform for applications and agents.

• Contribute to modeling and cost strategy development.

• Take on the role of technical lead for AI at GiveCampus and establish internal AI architecture standards.

• Make decisions regarding technical architecture and engineering for the platform.

• Support related projects such as front-end tools for internal use, adoption initiatives, and business workflow analysis.

• Report directly to the AI Transformation Lead.

• Collaborate with Engineering, Product, AI Plumbers, and departmental AI Taskforce builders.

⛳️ Requirements

• A minimum of six years of experience in software engineering, with significant experience managing platform, infrastructure, or backend systems in a production environment.

• Practical experience deploying LLM systems for real users, including functionalities like retrieval, tool usage, evaluations, and MCP or similar integration patterns.

• Proficiency in Python.

• Experience with cloud infrastructure, with a preference for AWS.

• Familiarity with authentication methods and observability practices.

• A security-oriented mindset focused on access control, data boundaries, and failure modes.

• Proven track record of developing internal platforms or shared services that have been widely adopted.

• Experience in evolving a system from an initial version to one relied upon by the entire company.

• Willingness to transition into the technical lead for AI across the organization.

• Up-to-date knowledge of AI and a commitment to ongoing learning.

• Orientation towards achieving business results.

• Ability to work based on requirements set in collaboration with a product partner and the judgment to question technical direction as needed.

• Strong written communication skills to engage effectively with both technical and non-technical team members.

• Nice to have: experience with agent orchestration, multi-agent systems, or agent governance tools.

• Nice to have: familiarity with Snowflake, dbt, or a semantic layer.

• Nice to have: experience with Salesforce data and APIs.

• Nice to have: experience in startup or small-team environments as the primary owner of a system.

🏝️ Benefits

• Team members have the flexibility to work from any location within the US.

• Access to a spacious 12,000-square-foot office in Washington, DC whenever desired.

• Regular team gatherings, visits to partner institutions, and retreats.

• A remote-first, flexible, and distributed work approach.

• A culture focused on sustainable growth.

• Participation in an employee liquidity event through the $140 million growth investment in 2025.

• A written culture that promotes asynchronous work, real autonomy, and direct access to leadership.

• A supportive, inclusive, and learning-centric environment.

• Equal Opportunity Employer.