International Rescue Committee
AI Platform Engineer
Remote · Full-time · United States
- Compensation
- Not defined
- Category
- AI engineering
- Employment
- Full-time
- Workplace
- Remote
Technologies
Python
TypeScript
- AI
About the role
The International Rescue Committee (IRC) responds to the world's worst humanitarian crises, helping to restore health, safety, education, economic wellbeing, and power to people devastated by conflict and disaster.
Founded in 1933 at the call of Albert Einstein, the IRC is one of the world's largest international humanitarian non-governmental organizations (INGO), at work in more than 40 countries and 29 U. S. cities helping people to survive, reclaim control of their future and strengthen their communities.
A force for humanity, IRC employees deliver lasting impact by restoring safety, dignity and hope to millions. If you're a solutions-driven, passionate change-maker, come join us in positively impacting the lives of millions of people world-wide for a better future.
Job Background / Overview The IRC is actively investing in enterprise AI to improve the speed, quality, and scale of its programs and operations.
As the organization expands its use of AI platforms, including tools from Anthropic, OpenAI, and integrated data environments, the IT department is building dedicated technical capacity to keep these systems running reliably, securely, and effectively.
The IRC is investing in enterprise AI to improve the speed, quality, and scale of its programs and operations. As that investment grows, so does the need for someone to own the technical layer underneath it: the systems, integrations, and infrastructure that make AI tools work at scale.
The AI Platform Engineer is that person. This is a technical operations role, not a user-facing one.
This role is responsible for keeping the IRC's enterprise AI environment running managing platform configurations and API access, building and maintaining integrations between AI tools and IRC systems, writing scripts and automations, and serving as the technical point of contact for data engineering and InfoSec.
Day-to-day, this person is more likely to be reading logs, troubleshooting a broken pipeline, or pushing a configuration change than answering questions from end users. The role works in close coordination with the AI Platform Support Director, who owns vendor relationships, licensing, and adoption strategy.
This role owns the technical execution underneath that, ensuring the systems are reliable, observable, and properly connected to the rest of the IRC's data and operational environment.
Major Responsibilities AI Systems Administration & Operations (40%) Serve as primary technical administrator across IRC enterprise AI environments, currently including Anthropic (Claude) and OpenAI platform deployments Manage user access, API key governance, workspace configurations, and environment-level settings across AI platforms Monitor system health, usage patterns, and API performance across AI tools; triage and resolve operational issues as they arise Maintain and improve observability across AI systems Tracking uptime, error rates, token consumption, and integration reliability Oversee and document configuration changes, environment updates, and deployment procedures across managed platforms Support responsible use by flagging anomalous usage patterns and coordinating with InfoSec on policy adherence and access controls Integrations & Technical Implementation (35%) Coordinate with the DevOps, SW Engineering and Data Engineering team(s) on deployment processes, environment access, and infrastructure dependencies required to build and maintain AI integrations Follow established change management procedures for all configuration changes, environment updates, and integration deployments, including documentation, testing, and appropriate approvals before pushing to production Develop lightweight scripts, connectors, and automations to support AI-assisted workflows across teams, primarily in Python and/or JavaScript/TypeScript Troubleshoot integration failures, data flow issues, and API connectivity problems across the AI ecosystem Collaborate with the data engineering team on AI/KM pipeline w