AI Solutions Engineer

Flooring Company; Eatontown (NJ); On-site; USD 120,000 - 160,000; Full time

Job summary

Flooring Company is seeking a technical role to observe real preconstruction workflows, redesign processes, and build automation that sticks across estimating, procurement, and project management tools. You will work with ownership and operations leadership to reduce cycle time and rework while enabling measurable improvements.

Ideal candidates have strong Python, LLM/API experience, and a track record of delivering end-to-end automation in document-heavy, multi-state environments like flooring

Qualifications

• Proven ability to design and implement document-heavy data pipelines.
• Experience integrating with construction software stacks lacking clean APIs.
• Ability to translate real-world workflows into automated processes.
• Experience conducting discovery conversations with estimators or project managers.
• Judgment about when to rely on deterministic code or simple automation over models.

Responsibilities

• Shadow current workflows across preconstruction, takeoff, buyout, submittals, RFIs, change orders, invoicing, and field coordination; document current state.

Skills

Python

LLM APIs

Prompt engineering

RAG

Structured outputs

Evaluation

Discovery conversations

Deterministic code

Tools

Procore

Sage

Viewpoint

Foundation

QuickBooks

M365/SharePoint

Bluebeam

AgTek

HCSS

B2W

Job description

Job Description

Job Description

The shape of the role Two-thirds field-and-process work, one-third build. You will sit with estimators, project managers, procurement, warehouse leads, and superintendents, watch how the work actually gets done, redesign the process, then build the automation that makes the new process stick. This is not a research role and not a pure software-development role.

What you will do

• Shadow real workflows across preconstruction, material takeoff and buyout, submittals (product data, SDS, samples), RFIs, change orders, AIA billing, daily reports, warehouse/inventory across multiple states, and field coordination. Document the current state — including the spreadsheets, email chains, and workarounds that never appear on the org chart.
• Re-engineer the process first: eliminate unnecessary steps and handoffs, decide what should be automated, what should be standardized, and what should be left alone.
• Build and ship working systems against real production data — document extraction and structured data from plan sets, specs, submittals, and invoices; agent-assisted workflows over email, SharePoint, and file shares; integrations that push clean data into estimating, ERP, or project-management tools.
• Instrument everything that matters: cycle time, error rate, rework, cost per run, adoption. If it cannot be measured, it is not considered shipped.
• Own the last mile — training, adoption, and rapid iteration when people use (or refuse to use) the tool differently than expected.

Must have

• Strong Python and practical experience with LLM APIs, prompt/context engineering, retrieval (RAG), structured outputs, and evaluation.
• Document-heavy pipelines: PDFs, scanned documents, tables, plan sets, product data sheets, and messy real-world inputs.
• Integration experience against systems that have limited or no clean APIs (common construction stack examples: Procore, Sage, Viewpoint, Foundation, QuickBooks, M365/SharePoint, and similar tools).
• Ability to run a discovery conversation with an experienced estimator or project manager and leave with the actual process, not the polished version.
• Clear judgment about when deterministic code, rules, or simple automation beats a model.

Nice to have

• Direct exposure to commercial construction, flooring/tile, or field-services operations.
• Familiarity with estimating/takeoff or project tools (Bluebeam, AgTek, HCSS, B2W, or equivalents).
• Process-improvement background (Lean, Six Sigma, or equivalent hard-won experience).

How we will evaluate

• Walk us through a real workflow you observed and redesigned — what you cut, what you automated, what changed in cycle time or quality, and how you got people to use it.
• Live exercise: given a set of construction documents (specs, product data, or a simplified plan/takeoff package), extract structured information and explain your approach, failure modes, and how you would harden it for production use.
• Show something you shipped that non-technical people use regularly.

About the opportunity

You will work directly with ownership and operations leadership at a mid-size commercial flooring and tile contractor that handles high-end multi-family and related projects across multiple states. The AI capability is being built deliberately; the person in this role will shape both the tools and the operating habits around them. High ownership, visible impact, and the chance to turn process friction into measurable operational improvement.