Applied Ai Specialist
Listed on 2026-10-16
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IT/Tech
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APPLIED AI SPECIALIST2 days ago Requisition
Summary
The Applied AI Specialist uses artificial intelligence to solve practical business problems. The work is applied rather than theoretical: building tooling that assembles reporting from the company's corporate operating systems so that business analytics improve, and developing tools that make each department's day-to-day work move faster and with better information.
This is an individual contributor position for someone who can take a defined problem and deliver a working, documented, production-ready solution. The Director of Business Intelligence sets departmental technical standards and carries governance and vendor decisions. Within those standards the person in this seat owns the design of their assigned solution areas.
Essential Duties and Responsibilities
Applied AI Development
- Build tooling that assembles reporting from the company's corporate operating systems and provides for better business analytics.
- Develop artificial intelligence tools that provide for more efficient workflows within each department's function.
- Design, build, test and deploy agents and assistants that automate research, document review and report preparation.
- Prototype quickly, measure each result against the process it replaces, and either harden it for production or retire it.
- Extract structured data from construction documents (drawings, specifications, contracts, submittals, schedules and meeting transcripts) using vision-capable and language models, so that downstream scheduling, estimating, contract and risk tools answer from the project record rather than from general knowledge.
- Write and maintain the integrations required to connect the company's platforms to one another and to artificial intelligence services.
- Design and maintain retrieval pipelines over company documents and project data, so that tooling answers from the company's own information rather than from general knowledge.
- Work with the Director on the company data warehouse, including ingestion, modeling and the interfaces that tooling queries against.
- Maintain source control, environment configuration, testing and deployment practice for everything built.
- Build and maintain connectors to the company's platforms using open agent protocols (Model Context Protocol or equivalent), reusable agent skills and scheduled agent runs, with a named service account for every integration.
- Treat the company data warehouse as the primary source for every assistant that reports numbers: tooling queries the governed model maintained by the Business Intelligence & Automation Analyst rather than re-deriving figures from raw files.
Evaluation & Production Operations
- Maintain a golden test set and regression suite for every deployed assistant. No prompt, model or retrieval change ships without passing it, and a failed check is reported, not suppressed.
- Instrument every assistant with tracing and logging so that each run's inputs, retrieved sources, outputs, latency and cost can be reviewed after the fact.
- Report monthly, per tool: accuracy against the test set, failure rate, adoption, time saved and API or token spend against the approved budget.
- Own production support for deployed assistants: monitoring, failure alerting, incident response, a published support path for end users, and a written runbook for each tool.
Standards, Governance & Security
- Apply and help refine the departmental standards for how tools are built, named, versioned, documented and shared inside the company.
- Build the required guardrails into every deployed tool, covering data handling, confidentiality, output accuracy and the boundary between a recommendation and a human decision.
- Contribute hands-on testing and written findings to platform and vendor evaluations led by the Director.
- Partner with Information Technology on security review, access control, licensing and acceptable use, and raise concerns early.
- Classify data before it reaches any model service. De-identify personnel and compensation data, keep client-confidential material inside approved services only, and confirm vendor data-retention and model-training terms before a new service is used.
- Route every automated read of company data through named, department-owned service accounts whose activity is logged and reviewed quarterly by the Director and the Executive Vice…
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