Onsite AI Engineer

Overview

Onsite AI Engineer — New Haven, CT — Fully onsite 5 days per week.

Role

Summary:

As the on-site catalyst who turns AI ideas into working reality, you will partner with project leaders (Project Managers and Superintendents) to uncover pain points, redesign workflows, and deploy multiple AI agents that reduce reporting overhead, accelerate RFIs, simplify planning, progress tracking, materials management, and more. You will work closely with the company s central AI Studio when advanced engineering support is needed, but your focus is on rapid, practical deployment of agents in the field.

This role is central to advancing the company s vision of the "Construction Site of the Future,” showing how agentic AI transforms daily project operations.

• Workflow discovery and redesign: Lead Lean/Six Sigma workshops; map value streams; log high-impact AI agent opportunities that improve field efficiency.
• AI agent development: Build and deploy multiple production-ready AI agents using Copilot Studio, Power Apps/Automate, ChatGPT Enterprise, or code-first frameworks. Integrate agents into Teams/SharePoint on the front end and Databricks Lakehouse or other enterprise data sources on the back end.
• RAG pipelines and LLMOps: Design and operate retrieval-augmented generation (RAG) pipelines with Databricks Delta Tables, Unity Catalog, and Vector Search (or Spark/Hadoop equivalents). Monitor cost, latency, adoption, and model drift.
• Cross-cloud orchestration: Blend OpenAI, Azure OpenAI, and AWS Bedrock services through secure custom connectors to maximize flexibility and adoption.
• Data integration: Partner with Data Engineering to deliver ETL/ELT pipelines, API integrations, and event-driven connectors that feed RAG pipelines and AI agents.
• Change management and adoption: Train field teams, gather feedback, iterate quickly, and embed agents into SOPs. Track usage and ROI with adoption metrics and behavior-change KPIs.
• Stakeholder communication: Translate technical results into business value for leadership and clients. Contribute use cases and playbooks for the "Construction Site of the Future.”
• Compliance and hand-offs: Ensure all AI solutions meet the company s data governance and security standards. Draft clear user stories and specs for escalation to central AI/Data Engineering teams when necessary.

• 4+ years in AI engineering, data science, or ML-focused software engineering.
• Proven experience building multiple AI agents in production environments.
• 2+ years of hands-on experience with LLMs, RAG pipelines, and LLMOps practices.
• Strong proficiency in Python, SQL, and Databricks (Spark/Hadoop equivalents acceptable).
• Hands-on experience with Copilot Studio, Power Apps/Automate, API development and integration.
• Familiarity with CI/CD, Git Hub Actions (or Azure Dev Ops), workflow automation.
• Solid understanding of ETL/ELT, REST/Graph
  
  QL APIs, and collaboration with Data Engineering teams.

• Experience in construction, manufacturing, or other process-heavy industries.
• Background in data engineering workflows (Airflow, ELT/ETL, etc).
• Advanced degree in a technical field.