Overview
This role is responsible for the technical operations of the IRC's enterprise AI environment, ensuring AI tools run reliably, securely, and effectively. It involves managing platform configurations, API access, and building integrations between AI tools and IRC systems.
Key Responsibilities
- Serve as primary technical administrator across enterprise AI environments (Anthropic, OpenAI).
- Manage user access, API key governance, workspace configurations, and environment-level settings.
- Monitor system health, usage patterns, and API performance; triage and resolve operational issues.
- Maintain and improve observability across AI systems.
- Oversee and document configuration changes, environment updates, and deployment procedures.
- Support responsible use by flagging anomalous usage patterns and coordinating with InfoSec.
- Coordinate with DevOps, SW Engineering, and Data Engineering teams on deployment processes and infrastructure.
- Develop lightweight scripts, connectors, and automations, primarily in Python and/or JavaScript/TypeScript.
- Troubleshoot integration failures, data flow issues, and API connectivity problems.
- Collaborate with the data engineering team on AI/KM pipeline work.
- Contribute to technical design discussions.
- Maintain technical documentation for all integrations.
- Track and report on AI resource utilization, identifying cost efficiency opportunities.
- Serve as the technical point of contact with the InfoSec team on system security, data handling, and compliance.
- Support risk assessments and security reviews.
- Contribute to the development of technical SOPs and best-practice guidelines.
- Act as a technical resource for program and operations teams adopting AI tools.
- Participate in rollout planning for new AI capabilities.
- Collaborate on onboarding documentation and technical guidance materials.
Required Experience
- 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.
- 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.
- Familiarity with version control (Git) and standard deployment practices.
- 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.
- 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.
- Ability to communicate technical concepts clearly to non-technical colleagues and program staff.
- Experience contributing to cross-functional teams.
