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

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