Site AI Engineer

Suffolk Construction Company, Inc. is a national builder that blends construction management with data, AI, and technology through its Seamless Platform. This on‑site Site AI Engineer role in Temple, TX turns AI ideas into deployed solutions on active project sites. You will partner with project AI Champions to redesign workflows and deploy AI agents that enhance reporting, RFIs, lookahead planning, progress updates, and materials tracking.

Location: Temple, TX (onsite)

Benefits

• Competitive salaries
• Auto allowances and gas cards for certain roles
• Market leading medical coverage plus emotional and mental health benefits
• Dental insurance
• Vision insurance
• Virtual care options for physical therapy and primary care
• Generous paid time off
• 401k plan with employer match
• Access to expert financial resources
• Company paid and voluntary life insurance
• Tax deferred savings accounts
• 10 backup daycare days each year
• Short-term and long-term disability
• Commuter benefits

Responsibilities

• Opportunity discovery and workflow redesign — Lead discovery sessions, map value streams, assess process and data maturity, and log low‑effort/high‑impact AI use cases.
• Process and data maturity assessment — Evaluate jobsite workflows and data, surface gaps that block AI adoption, and develop phased improvement plans with Operations Excellence to establish the baseline before deploying agents.
• Assess 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, connecting front end to Teams/SharePoint and back end to Databricks Lakehouse, AWS services, or other sources.
• Enterprise‑grade engineering & LLMOps — Build Agentic RAG pipelines backed by OpenSearch and other data stores; automate infrastructure with GitHub 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 services, 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 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 complex solutions needing central AI Solution Engineers or Data Engineering / Data Science teams to enable scaling; collaborate to turn prototypes into enterprise‑ready applications.
• Compliance — Ensure on‑site AI tools meet Suffolk’s information security, data governance, and client confidentiality standards.

Requirements

• 4–6+ years in AI engineering, full‑stack data applications, or data science, including at least 2 years building production LLM, RAG, or agentic solutions.
• Bachelor’s degree in computer science, engineering, physics, or a related field; Master’s preferred.
• Hands‑on experience in construction or heavy process industries (manufacturing, oil & gas, chemicals) is a significant plus.
• Proven process excellence background (Lean/Six Sigma Green Belt a plus) with experience diagnosing process and data gaps and supporting change management plans with Operations Excellence.
• Strong facilitation and communication skills.
• Hands‑on experience with Claude Code, Devin AI, MS Copilot, and other coding assistants.
• Programming and data stack: Python, SQL, Fast API, Databricks Lakehouse, vector stores.
• DevOps and IaC: GitHub Actions, Terraform or CloudFormation automation, or similar CI/CD tooling; solid Git/GitHub discipline.
• Integration and ETL skills: understanding of ETL/ELT design, Airflow or Databricks Workflows, REST/GraphQL API development; proven collaboration with Data Engineering on source‑to‑lake and lake‑to‑agent pipelines.
• Willing and able to travel and work on active jobsites.

Technologies

• Python
• SQL
• Fast API
• Databricks Lakehouse
• Vector stores
• GitHub Actions
• Terraform
• CloudFormation
• Airflow
• REST
• GraphQL
• AWS Bedrock
• Sagemaker
• ChatGPT Enterprise
• OpenAI
• Azure OpenAI
• OpenSearch
• Teams
• SharePoint
• Databricks Workflows
• Claude Code
• Devin AI
• MS Copilot