Hands-on cloud deployment experience (Azure preferred, AWS, Snowflake, Databricks): compute, storage, managed databases, container services, and identity/access management + Experience working with messy, real - world data and legacy systems AI & LLM Engineering + Hands-on experience building and deploying LLM applications: RAG pipelines, vector store management (Pinecone, pgvector, or Weaviate), embedding workflows, and API integration using Anthropic, OpenAI, or Azure OpenAI SDKs + Experience implementing AI evaluation frameworks (e.g., LangSmith, Arize, or custom evals) to monitor model outputs, detect drift, and enforce output quality in production + Experience deploying AI applications to cloud infrastructure (Azure, AWS, or GCP), including containerization (Docker), serverless functions, and SSO/identity integration for enterprise tool rollout Communication & Collaboration + Strong listening skills and ability to clarify ill - defined problems + Ability to communicate effectively with technical peers, non - technical staff, and executive leadership + Proven ability to build trust across departments with competing priorities Nice to Have + Experience with ERP systems in professional services or project - based organizations + Familiarity with data governance frameworks or formal data quality practices + Experience working in AEC, design, or creative professional environments + Background in internal training, enablement, or change management Why This Role Matters This is an opportunity to shape how a globally recognized design firm uses data and AI - not as novelty, but as durable infrastructure that supports better decisions, better work, and better outcomes. What You Will Do AI Tool Deployment & Enablement + Build, deploy, and support the maintenance and updates of our firm's custom-built large language model (LLM) for Project Managers, currently in beta testing, as well as the creation of new LLMs for operational teams (e.g., Marketing, Legal, Resource Planning, Finance).