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 system

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 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