Site AI Engineer

Suffolk Construction Company, Inc.; Temple (TX); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Competitive salaries

Auto allowances and gas cards

Medical and mental health benefits

Dental and vision insurance

Virtual care options

Generous paid time off

401(k) with employer match

Life insurance

Tax deferred savings accounts

Backup daycare days

Disability insurance

Commuter benefits

Job summary

Suffolk Construction Company, Inc. is seeking a Site AI Engineer to act as an on-site catalyst, turning AI ideas into practical solutions across project teams.

You will collaborate with AI Champions, redesign workflows, deploy agents, and coordinate with the central AI Studio to scale prototypes into enterprise-ready applications. Responsibilities include discovering pain points, drafting user stories, leading pilots, and ensuring security and governance standards on-site.

Qualifications

• 4–6+ years in AI engineering or data science with production experience
• Bachelor’s degree required; Master’s preferred
• Experience in construction or heavy industry is a plus

Responsibilities

• Identify AI opportunities and redesign workflows on active job sites
• Draft user stories and coordinate with AI Studio for prototypes
• Lead pilots, measure impact, and scale successful deployments
• Ensure on-site AI tools meet security and governance standards

Skills

Strong facilitation

Communication skills

On-site collaboration

Education

Bachelor’s degree in CS, Engineering, Physics, or related field

Master’s degree preferred

Tools

Claude Code

Devin AI

MS Copilot

GitHub Actions

Terraform

CloudFormation

Airflow

Databricks Lakehouse

SageMaker

Bedrock

Job description

What Suffolk Construction offers

Suffolk supports you with a comprehensive total rewards program designed to sustain you and your family physically, emotionally, and financially. Expect competitive pay and a robust benefits package that prioritizes wellness, financial security, and work-life balance.

• Competitive salaries
• Auto allowances and gas cards for certain roles
• Market-leading medical and mental health benefits
• Dental and vision insurance
• Virtual care options for physical therapy and primary care
• Generous paid time off
• 401(k) with employer match
• Company paid and voluntary life insurance
• Tax deferred savings accounts
• Backup daycare days
• Short- and long-term disability
• Commuter benefits

Location and role context

Location: Temple, Texas, on-site

As a Site AI Engineer on Suffolk’s construction projects, you act as an on-site catalyst who turns AI ideas into functioning solutions. You partner with AI Champions to redesign workflows, deploy AI agents, and coordinate with the central AI Studio to advance the Construction Site of the Future.

Role overview

You will work across project teams as the on-site AI catalyst, uncovering pain points, simplifying reporting, speeding RFIs, supporting lookahead planning, materials tracking, and more. When needed, you draft user stories and coordinate development with the central AI Studio to scale prototypes into enterprise-ready applications.

Responsibilities

• Identify opportunities and redesign workflows by leading discovery, mapping value streams, assessing process and data maturity, and logging high-impact, low-effort AI use cases
• Assess current jobsite workflows and underlying data; surface gaps blocking AI adoption and develop phased improvement plans with Operations Excellence to establish the right baseline before deploying agents
• Evaluate off-the-shelf and platform tools; run pilots, measure impact, and scale successful deployments
• Translate user stories into MVP AI agents using AWS Bedrock/SageMaker, ChatGPT Enterprise, and other frameworks within days; connect front-end to Teams/SharePoint and back-end to Databricks Lakehouse, AWS services, or other sources
• Build enterprise-grade Agentic RAG pipelines backed by Opensearch and other data stores; automate infrastructure with GitHub Actions; monitor latency, cost, adoption, and drift
• Collaborate with Data Engineering to design and maintain ETL pipelines, API integrations, and event-driven connectors feeding RAG and agents
• Orchestrate across AWS Bedrock, OpenAI, and Azure OpenAI behind secure connectors; package agents for seamless rollout
• Provide change enablement through training, feedback loops, iteration, and tracking adoption and ROI metrics; embed agents into daily routines and SOPs with a focus on behavior change KPIs
• Brief project leadership and clients on agent impact in business terms; contribute use cases and playbooks for Suffolk’s Construction Site of the Future
• Draft clear user stories, data specs, and acceptance criteria for complex solutions requiring central AI Solution Engineers or Data Engineering / Data Science teams; collaborate to scale prototypes into enterprise-ready solutions
• 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 2+ years building production LLM, RAG, or agentic solutions
• Bachelor’s degree in CS, 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
• Demonstrated process excellence background; Lean/Six Sigma Green Belt a huge plus; experience diagnosing process and data gaps and supporting change management with Operations Excellence
• Strong facilitation and communication skills
• Hands-on expertise with Claude Code, Devin AI, MS Copilot, and other coding assistants
• Programming and data stack: Python, SQL, FastAPI, Databricks Lakehouse, vector stores
• DevOps and IaC: GitHub Actions, Terraform or CloudFormation automation, or comparable CI/CD tooling; strong Git/GitHub workflow discipline
• Foundational ETL/ELT design knowledge, Airflow or Databricks Workflows, and 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 job sites

Technologies

• Python
• SQL
• FastAPI
• Databricks Lakehouse
• Databricks Workflows
• AWS Bedrock
• Amazon SageMaker
• ChatGPT Enterprise
• Microsoft Teams
• SharePoint
• OpenAI
• Azure OpenAI
• OpenSearch
• GitHub Actions
• Terraform
• CloudFormation
• Airflow
• REST
• GraphQL
• Vector stores

Working conditions

The role is performed on-site at active job sites and in an office environment with a quiet to moderate noise level. The position requires time on site, including occasional job site walking, and may involve travel.