AI Platform Engineer

Description

A humanitarian nonprofit founded in 1933 that operates in more than 40 countries and 29 U.S. cities. It helps people hit by conflict and disaster recover their health, safety, education, economic wellbeing and control over their lives.

The company is putting enterprise AI into its programs and operations to make them faster, better and able to reach more people. Its IT department is building the technical capacity to keep its AI platforms reliable, secure and effective, including tools from Anthropic and OpenAI and its integrated data environments.

This is a technical operations role, not a user-facing one. You will keep the enterprise AI environment running by managing platform configurations and API access, building integrations between AI tools and company systems, writing scripts and automations, and acting as the main technical contact for data engineering and InfoSec. Much of your day will be spent reading logs, fixing broken pipelines or pushing configuration changes rather than answering end user questions.

You will work closely with the AI Platform Support Director, who owns vendor relationships, licensing and adoption strategy. You own the technical execution beneath that, keeping systems reliable, observable and well connected to the company's data and operational environment.

Responsibilities

• AI systems administration and operations (40%): Act as the primary technical administrator for the company's enterprise AI environments, currently the Anthropic (Claude) and OpenAI platform deployments.
• Manage user access, API key governance, workspace settings and environment-level configuration across AI platforms.
• Monitor system health, usage patterns and API performance, and triage and resolve operational issues as they arise.
• Improve observability across AI systems by tracking uptime, error rates, token consumption and integration reliability.
• Document configuration changes, environment updates and deployment procedures for every managed platform.
• Flag unusual usage patterns and work with InfoSec on policy adherence and access controls.
• Integrations and technical implementation (35%): Work with the DevOps, software engineering and data engineering teams on deployment processes, environment access and the infrastructure AI integrations depend on.
• Follow change management procedures for every configuration change, environment update and integration deployment: document, test and get approval before anything reaches production.
• Build lightweight scripts, connectors and automations that support AI-assisted workflows across teams, mainly in Python and/or JavaScript/TypeScript.
• Troubleshoot integration failures, data flow problems and API connectivity issues across the AI ecosystem.
• Work with data engineering on AI and knowledge management pipelines, including vector store ingestion, retrieval configuration and source data connections.
• Take part in technical design discussions, turning operational needs into solutions engineering partners can build.
• Maintain technical documentation for every integration, including architecture notes, runbooks and dependency maps.
• Monitoring, resource optimization and InfoSec liaison (15%): Track AI resource use across platforms, find waste and cost savings, and coordinate on these in coordination with the AI team.
• Serve as the technical point of contact for InfoSec on AI system security, data handling, access controls and compliance requirements.
• Give accurate technical context on system behavior and data flows to support security reviews and risk assessments of new AI tools and integrations.
• Help write technical SOPs and best-practice guidelines for AI system use, working with the AI Platform Support Director and other stakeholders.
• Stakeholder support and collaboration (10%): Act as a technical resource for program and operations teams adopting AI tools by answering implementation questions, supporting troubleshooting and identifying configuration fixes.
• Provide grounded input on technical feasibility, integration requirements and operational readiness when planning rollouts of new AI capabilities.
• Work with the AI Platform Support Director on onboarding documentation and technical guidance for end users.
• Contribute to sprint and project planning with accurate estimates of technical effort and dependencies.

Requirements

• Hands-on experience administering enterprise AI platforms such as Anthropic, OpenAI, Azure OpenAI or comparable tools, including API management, access controls and environment configuration.
• Familiarity with LLM application infrastructure: prompt pipelines, Model Context Protocol (MCP), other tool-calling integration frameworks, vector databases, retrieval-augmented generation (RAG) patterns and embedding workflows.
• Experience with Databricks or comparable data/ML platforms (a strong plus).
• Proficiency in Python and/or JavaScript for scripting, automation and lightweight integration work.
• Experience building and maintaining REST API integrations, including authentication, webhook handling and error management.
• Able to read and work within existing codebases without significant architectural guidance.
• Familiarity with Git and standard deployment practices for scripts and integrations.
• Experience monitoring distributed systems or SaaS platforms, including setting up alerts, reviewing logs and diagnosing performance or availability problems.
• Familiarity with usage and cost monitoring for cloud or API-based services.
• Comfortable operating in live production environments where reliability and data integrity are critical.
• Working knowledge of information security principles for SaaS and API-based systems: access controls, credential management, data handling and audit logging.
• Able to engage constructively with InfoSec teams, giving clear technical context to support reviews and risk assessments.
• Able to explain technical concepts clearly to non-technical colleagues and program staff.
• Experience contributing to cross-functional teams alongside product, engineering and operations stakeholders.
• Strong documentation habits, including runbooks, SOPs, architecture notes and internal guides.

Conditions

This role is remote, with possible in-person work depending on your location.

Stakeholders are spread across time zones from GMT-8 to GMT+3, so occasional early or late meetings may be needed.

Annual pay range: $88,277 to $102,451. The range reflects the labor market, job type, internal equity and budget, and final offers depend on work location and your experience and skills relative to the role's requirements.

Staff are expected to follow the company's professional conduct standards and related policies, including safeguarding and conflict of interest rules.

Benefits

• 10 days of paid sick leave and 10 U.S. holidays.
• 20 to 25 days of paid time off, depending on role and tenure.
• Medical insurance from $163 per month, dental from $6.50 per month and vision from $5 per month.
• Flexible spending accounts for healthcare, dependent care and commuting.
• 403(b) retirement plan with an employer match that vests immediately, plus a non-elective employer contribution based on age and years of service that vests over 3 years.
• Disability and life insurance.
• Employee Assistance Program with confidential counseling and support for employees and their families.