AI Platform Engineer

GiveCampus

. Design, build, and operate GiveCampus's next generation of AI infrastructure .

Posted 11/6/2026full-timeRemote • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and operating AI infrastructure, with a strong focus on platform engineering, cloud services, and security practices. Capable of leading technical architecture decisions and fostering collaboration across teams to drive AI initiatives.

Highest-signal resume keywords

Software Engineering ExperienceStrong PythonCloud Infrastructure (AWS)AI Systems DevelopmentTechnical Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringAI Infrastructure DesignLLM Systems ShippingAuthenticationObservabilityData Leak PreventionAgent OrchestrationMulti-Agent SystemsInternal Platform DevelopmentBusiness-Results Orientation

Soft Skills

Clear Written CommunicationJudgment in Technical Direction

Tools & Technologies

AWSSnowflakeDbtSalesforce APIs

Industry Keywords

AI Architecture StandardsGovernanceMCP Integration PatternsAudit TrailsMonitoring

Tech Stack

Tools & technologies

AWSCloudPythonSnowflake

About the role

Key responsibilities & impact

Design, build, and operate GiveCampus's next generation of AI infrastructure
Build shared company and Partner context and memory used across agents
Establish identity, access, auditable permissions, credentials, and MCP connection management
Create a registry of existing AI tools and systems
Build governance including production evaluation gates, audit trails, monitoring, prompt-injection protection, and data-leak prevention
Make build-versus-buy decisions with Infrastructure
Develop templates and guardrails for Taskforce builders
Measure AI impact by department
Develop agents that run end-to-end processes and increase agent autonomy over time
Build an internal deployment platform for apps and agents
Contribute to model and cost strategy
Become the technical lead for AI across GiveCampus and set internal AI architecture standards
Make technical architecture and engineering decisions for the platform
Support adjacent work such as internal-tool front ends, adoption builds, and business-workflow analysis
Report to the AI Transformation Lead
Partner with Engineering, Product, AI Plumbers, and departmental AI Taskforce builders

Requirements

What you’ll need

Six or more years of software engineering experience, including meaningful time owning platform, infrastructure, or backend systems in production
Hands-on experience shipping LLM systems with real users, including retrieval, tool use, evaluations, and MCP or similar integration patterns
Strong Python
Experience with cloud infrastructure, AWS preferred
Experience with authentication and observability
Security mindset covering access, data boundaries, and failure modes
Record of building internal platforms or shared services adopted by others
Experience growing a system from an early version into something a whole company depends on
Appetite to grow into the technical lead for AI across the company
Current knowledge of AI and commitment to continued learning
Business-results orientation
Comfort working from requirements set with a product partner and judgment to challenge technical direction when appropriate
Clear written communication with technical and non-technical teammates
Nice to have: experience with agent orchestration, multi-agent systems, or agent governance tooling
Nice to have: familiarity with Snowflake, dbt, or a semantic layer
Nice to have: experience with Salesforce data and APIs
Nice to have: startup or small-team experience as the first owner of a system

Benefits

Comp & perks

Team members work from anywhere they choose within the US
Access to a 12,000-square-foot Washington, DC office whenever desired
Regular team meet-ups, partner institution visits, and retreats
Remote-first, flexible, distributed work
Sustainable Growth culture
Employee liquidity event participation through the 2025 $140 million growth investment
Written culture with async work, real autonomy, and direct access to leadership
Supportive, inclusive, and learning-focused environment
Equal Opportunity Employer