AI Platform Engineer

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 systemsTracking 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 work, including vector store ingestion, retrieval configuration, and source data connections
• Contribute to technical design discussions with engineering partners, translating operational requirements into implementable solutions
• Maintain technical documentation for all integrations, including architecture notes, runbooks, and dependency maps

Monitoring, Resource Optimization & InfoSec Liaison (15%)

• Track and report on AI resource utilization across platforms, identifying opportunities to reduce waste and improve cost efficiency in coordination with the AI 
• Serve as the technical point of contact with the InfoSec team on matters related to AI system security, data handling, access controls, and compliance requirements
• Support risk assessments and security reviews for new AI tools or integrations by providing accurate technical context on system behavior and data flows
• Contribute to the development of technical SOPs and best-practice guidelines for AI system use, in coordination with the AI Platform Support Director and relevant stakeholders

Stakeholder Support & Collaboration (10%)

• Act as a technical resource for program and operations teams adopting AI tools, including answering implementation questions, supporting troubleshooting, and identifying configuration solutions
• Participate in rollout planning for new AI capabilities, providing grounded input on technical feasibility, integration requirements, and operational readiness
• Collaborate with the AI Platform Support Director on onboarding documentation and technical guidance materials for end users
• Contribute to sprint and project planning with accurate estimates on technical effort and dependencies

Required Experience & Skills

AI & Cloud Platforms

• Hands-on experience administering enterprise AI platforms (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 working with Databricks or comparable data/ML platforms is a strong plus

Integration & Development

• Proficiency in Python and/or JavaScript for scripting, automation, and lightweight integration work
• Experience building and maintaining REST API integrations, including authentication patterns, webhook handling, and error management
• Comfort reading and working within existing codebases without requiring significant architectural guidance
• Familiarity with version control (Git) and standard deployment practices for scripts and integrations

Systems Administration & Monitoring

• Experience monitoring distributed systems or SaaS platforms, including setting up alerting, reviewing logs, and diagnosing performance or availability issues
• Familiarity with usage/cost monitoring for cloud or API-based services
• Comfort operating in live production environments where reliability and data integrity are critical

Security & Compliance

• Working knowledge of information security principles as they apply to SaaS and API-based systems: access controls, credential management, data handling, and audit logging
• Ability to engage constructively with InfoSec teams, providing clear technical context to support reviews and risk assessments

Collaboration & Communication

• Ability to communicate 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: runbooks, SOPs, architecture notes, and internal guides