Site AI Engineer - Temple, TX

Site AI Engineer - Temple, TX Overview

About Suffolk - a national enterprise that builds, innovates and invests. We provide value across the entire project lifecycle through our core construction management services and complementary business lines in real‑estate investment, design, self‑perform construction, and technology start‑up investment (Suffolk Technologies). By integrating data, artificial intelligence, and advanced technology through our Seamless Platform, we connect design, construction, and operations to deliver smarter, more predictable results and redefine how America builds.

Suffolk is a national company with more than $9 billion in annual revenue, 3,000 employees, and 17 offices, including Boston (headquarters), New York City, Miami, West Palm Beach, Tampa, Estero, Dallas, Los Angeles, San Francisco, San Diego, Las Vegas, Herndon, U.S. Virgin Islands, and other key markets. Suffolk manages some of the most complex and transformative projects in the country, serving clients across healthcare, life sciences, education, gaming, aviation, transportation, government, mission critical, and commercial sectors.

Suffolk is privately held and is led by founder, chairman and CEO John Fish. Suffolk is ranked #8 on ENR’s list of “Top CM‑at‑Risk Contractors.” For more information, visit

Join Suffolk’s project teams across the U.S. as the on‑site catalyst who turns AI ideas into working reality. Partnering with each project’s AI Champion (Project Manager or Superintendent), you’ll uncover pain points, redesign workflows, and deploy AI agents that cut down reporting, accelerate RFIs, simplify lookahead planning, progress updates and materials tracking. When needed, you will develop user stories and coordinate development with the central AI Studio.

You’ll help advance the vision of the “Construction Site of the Future,” showing how agentic AI will transform project operations.

Location:

Temple, TX.

• Opportunity hunting and workflow redesign – Lead discovery; map value streams, assess process and data maturity, and log low‑effort/high‑impact AI use cases.
• Process and data maturity assessment – Evaluate jobsite’s current workflows and underlying data; surface gaps that block AI adoption and develop phased improvement plans with Operations Excellence to establish the right process baseline before deploying agents.
• Assess the market solutions – Evaluate off‑the‑shelf and platform tools; launch pilots, measure impact and scale wins.
• Rapid AI‑agent builds – Convert user stories into MVP agents in AWS Bedrock/Sagemaker, ChatGPT Enterprise and other frameworks within days, with heavy use of AI coding assistants; wire them to Teams/SharePoint on the front end and Databricks Lakehouse, AWS services or other sources on the back end.
• Enterprise‑grade engineering & LLMOps – Build Agentic RAG pipelines backed by Open search and other data stores; automate infra with Git Hub Actions; monitor latency, cost, adoption and drift.
• Data integrations – Partner with Data Engineering to design and maintain ETL pipelines, API integrations and event‑driven connectors feeding RAG and agents.
• Cross‑cloud orchestration – Blend AWS Bedrock, OpenAI and Azure OpenAI behind secure custom connectors; package agents for seamless rollout.
• Change enablement – Train crews, gather feedback, iterate, and track adoption and ROI metrics; apply influence model principles to embed agents into daily routines and SOPs and track behavior change KPIs.
• Stakeholder communication – Brief project leadership and clients on agent impact in clear business terms; contribute use cases and playbooks for Suffolk’s “Construction Site of the Future.”
• Escalation & hand‑off – Draft clear user stories, data specs and acceptance criteria for any complex solution that requires the central AI Solution Engineers or Data Engineering/Data Science teams; work closely with those teams to turn prototypes into enterprise‑ready scaled applications.
• Compliance – Ensure every on‑site AI tool meets Suffolk’s information security, data governance and client confidentiality standards.

• 4‑6+ years in AI engineering, full‑stack data applications or data…