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Develops AI solutions for automated construction take-off and estimation using computer vision, deep learning, NLP, and multimodal models. Responsibilities include processing blueprints, PDFs, and SVGs; prototyping, optimizing, validating, and deploying models; applying data-centric and reproducible ML practices; and collaborating with engineering and product teams. The role requires production-ready Python development, experimentation, research evaluation, and containerized cloud deployment.

Develop and execute manual and automated test cases across unit, integration, acceptance, web, mobile, and API testing. Maintain automation scripts, contribute to testing frameworks, support shift-left practices, and collaborate with Product and Development teams during UAT and Scrum activities. Investigate production issues using application behavior, APIs, logs, data, and configurations. Apply AI-assisted QA tools for test generation, failure analysis, regression optimization, and coverage improvement.

Own the organization’s DevOps architecture, cloud-native infrastructure, CI/CD ecosystem, infrastructure-as-code strategy, observability frameworks, and container orchestration platforms. Design scalable GCP/AWS environments, Kubernetes deployments, deployment and rollback strategies, security practices, and reusable automation. Partner with engineering, AI, testing, and product teams, govern tooling decisions, and maintain architectural documentation, runbooks, and reference architectures.

Develop and deploy AI systems for automated construction take-off and estimation using computer vision, image processing, deep learning, NLP, and multimodal models. Build models that extract insights from blueprints, scanned PDFs, and SVG files; apply reproducible data science practices; optimize models for production; and collaborate with engineering, research, and product teams. The role also involves experimentation, model validation, rapid prototyping, and evaluating new AI research for construction applications.

Own the product vision, roadmap, delivery, and business outcomes for a customer segment in a vertical SaaS platform. Conduct customer research, define requirements, collaborate with design and engineering, analyze product and revenue metrics, improve adoption and retention, align stakeholders, and mentor an Associate Product Manager.

Lead end-to-end product design for AI-powered construction estimating software. Translate requirements into wireframes, prototypes, and high-fidelity designs; conduct user research and usability testing; contribute to design systems; collaborate with engineers, product managers, and program managers; present concepts to stakeholders; and drive projects from problem definition through polished UI and documentation.

Conduct high-volume outbound prospecting through calls, voicemails, and personalized emails to construction and field-services prospects. Qualify inbound and outbound leads, book product demos, manage early-stage pipeline, and support opportunity progression. Collaborate with marketing, data, product, and RevOps teams to refine messaging, improve targeting, maintain CRM accuracy, track KPIs, and provide prospect feedback.

Build and operate end-to-end MLOps infrastructure for computer vision, NLP, and multimodal models. Responsibilities include developing training and inference pipelines, containerized deployments, CI/CD, experiment tracking, model versioning, monitoring, observability, rollback, infrastructure as code, and model optimization. Collaborate with research, backend, and product teams to productionize AI systems while improving reliability, scalability, latency, and cost efficiency.

Own a portfolio of 15–25 strategic enterprise accounts, driving adoption, retention, renewals, and expansion. Lead onboarding, implementation, QBRs, executive relationships, ROI reporting, and strategic account planning. Partner with Sales and Product to identify growth opportunities, negotiate renewals, and communicate customer feedback. The role manages construction-industry customers and requires 40–50% travel for customer visits, QBRs, and trade shows.

Supports sales teams as a technical expert for AI-powered construction and landscaping software. Represents the company on customer calls, clarifies technical requirements, translates engineering concepts for sales professionals, communicates customer needs to estimating and product teams, develops training materials, supports enterprise pilots, and collaborates cross-functionally while working US time-zone hours.