Jobs at Scaffold

Lead technical customer implementations, configure integrations with builder portals and contractor ERPs, tailor workflows, and serve as the primary technical contact during onboarding and early adoption. Translate customer needs into product improvements, create documentation and training materials, and collaborate with engineering and product teams to resolve issues and accelerate customer value.

Design, build, and deploy production machine learning systems across workflow automation, data enrichment, predictive insights, and agent-based workflows. Own the full ML lifecycle, including data ingestion, model training, evaluation, deployment, and feedback loops. Integrate AI into backend services, APIs, data pipelines, and customer-facing products while shaping architecture and long-term AI strategy. Collaborate with product, engineering, and customers to deliver scalable, reliable AI solutions.

Own technical solution design from pre-sale through implementation handoff. Lead discovery workshops, assess integrations, map data and workflows, create implementation plans and solution documentation, and advise customers and internal teams on architectural decisions. Collaborate with product and engineering on feasibility and roadmap feedback, develop reusable solution playbooks, and support early adoption. The role requires strong Python, SQL, API, ETL, ERP, communication, stakeholder facilitation, and consultative skills.

Build and scale full-stack systems for residential construction data orchestration. The role emphasizes Python backend development, AI/ML solutions, third-party integrations, platform reliability, and performance. Responsibilities also include front-end contributions, architectural decision-making, code reviews, mentoring, and improving engineering processes. As an early startup team member, the engineer will collaborate closely with founders and stakeholders to define technical direction and deliver innovative products.

Lead the architecture and development of scalable data pipelines and infrastructure. Clean, standardize, and model construction data; build tools for data quality and performance; design integration flows with product, engineering, and customers; apply Python, SQL, and ETL practices; and use AI/ML to improve data classification and mapping. Establish data governance and reliability standards in a high-ownership startup environment.

Leads new-customer onboarding from kickoff through activation, coordinating timelines, milestones, technical implementation, training, communication, and stakeholder alignment. Owns customer relationships, translates requirements between customers and internal engineering and product teams, resolves blockers, and manages multiple concurrent engagements. As the first Implementation Manager, this role will also establish onboarding processes, playbooks, and best practices before handing activated customers to Customer Success.