Jobs at Attentive.ai

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.

Develop and maintain backend software, internal tools, consumer-facing applications, and ML/AI processing pipelines. Own development and production pipelines, build scalable systems, improve reliability and performance of deep learning and geoprocessing services, and create monitoring and logging infrastructure. Translate product requirements into technical designs and readable code, collaborate on data processing solutions, and lead junior developers through code reviews and quality practices.

Develop and maintain backend products, internal tools, and AI/geoprocessing pipelines. Own production systems, design scalable architectures, improve reliability and performance, implement monitoring infrastructure, collaborate on data pipelines, and lead junior developers through code reviews and quality practices.

Supports product strategy, roadmap prioritization, customer research, requirements documentation, backlog management, and cross-functional delivery for an AI-powered construction estimating product. Analyzes usage data and KPIs, supports experimentation, coordinates with engineering, design, sales, customer success, and marketing, and develops expertise in construction estimation and AI technologies.

Build, maintain, and optimize Webflow websites and landing pages across desktop and mobile. Manage CMS content, create reusable components, implement GSAP animations, improve performance and Core Web Vitals, conduct website audits, resolve bugs, and collaborate with SEO, design, product, and marketing teams. The role also involves UI/UX improvements, technical SEO support, AI-assisted workflows, and automating repetitive tasks.

Develop and execute sales strategies to identify and close new B2B SaaS customers. Build and manage sales pipelines, qualify inbound and outbound leads, engage key decision-makers through consultative selling, negotiate deals, and maintain customer relationships. Collaborate with product and marketing teams, while staying knowledgeable about the platform, construction industry, and relevant market trends.

Lead customer onboarding, product adoption, account management, renewals, and churn prevention for Beam AI’s construction software. Serve as the technical liaison between customers and the estimating team, explain construction requirements, track CSAT, NPS, renewals, and churn, identify upsell opportunities, and develop customer advocacy through case studies, testimonials, and referrals. The role requires construction or engineering expertise and customer-facing experience with US or Canadian clients.

Manage daily office administration, facilities coordination, vendor relationships, inventory and procurement, business travel bookings, and company events. The role ensures a smooth workplace experience by maintaining office infrastructure, tracking supplies and merchandise, coordinating repairs and services, supporting employee and leadership travel needs, and organizing meetings and engagement activities.

Manage customer onboarding, training, adoption, support, renewals, and account growth for a B2B SaaS construction takeoff product. Identify upsell opportunities, reduce churn, gather product feedback, support customer advocacy, and track success metrics including CSAT, NPS, renewals, and churn. The role requires strong communication, analytical, relationship-building, and problem-solving skills, with availability for US business hours and possible onsite customer travel.

Conduct applied AI research and development for construction take-off and estimation using computer vision, NLP, deep learning, and multimodal models. Build production-ready systems that extract insights from blueprints, scanned PDFs, SVGs, and other unstructured documents. Prototype, validate, optimize, and deploy models while collaborating with software engineering, research, and product teams. Apply data-centric practices, experiment tracking, reproducibility, and model optimization techniques.

Conduct applied computer vision and deep learning research for automated construction drawing takeoff and estimation. Own a scoped research problem, train and evaluate models for detection, segmentation, or structured extraction, explore self-supervised learning and multimodal signals, develop prototypes using real data, design evaluations, and present findings to the research team.