AI Engineer

Responsibilities

• Internal AI & Knowledge Tools
• Build, deploy, and maintain internal AI agents and intelligent search tools to answer common organizational questions using internal documents, standards, pricing models, policies, and naming conventions.
• Process & Workflow Automation: Automate repetitive business workflows by building agentic systems capable of executing multi-step, autonomous actions across multiple internal tools.
• Systems & Platform Integration: Extend existing back-office platforms (e.g., Monday.com, Microsoft 365, SharePoint, Ironclad, and other SaaS tools) by building custom integrations with AI models, APIs, databases, and document repositories.
• Document Intelligence & Content Generation: Automate document review, comparison, summarization, data extraction, classification, and creation.
• Build automated templates, prompts, and workflows for recurring deliverables like RFPs, RFIs, proposals, reports, and presentations.
• Custom Application Development: Rapidly design and deploy lightweight internal applications, web tools, and scripts when off-the-shelf software falls short.
• Technical Leadership & Strategy: Serve as the internal AI lead—identifying high-impact automation opportunities, evaluating the AI features of software during procurement, and determining when to build custom tools versus buying existing solutions.
• Infrastructure, Security & Governance: Establish reusable AI infrastructure, tool-calling patterns, permissions, logging, security frameworks, and evaluation methods, while developing clear organizational AI best practices.
• Support & Iteration

Languages