Construction is the 2nd largest industry in the world (4x the size of SaaS!). But unlike software (with observability platforms such as AppDynamics and Datadog), construction teams lack automated feedback loops to help projects stay on schedule and on budget. Without this observability, construction wastes a whopping $3T per year because glitches aren’t detected fast enough to recover.
Doxel AI exists to bring computer vision to construction, so the industry can deliver what society needs to thrive. From hospitals to data centers, from foreman to VPs of construction, teams use Doxel to make better decisions everyday. In fact, Doxel has contributed to the construction of the facilities that provide many of the products and services you use everyday.
We have classic computer vision, deep learning ML object detection, a low-latency 3D three.js web app, a complex data pipeline powering it all in the background. We’re building out new workflows, analytics dashboards, and forecasting engines.
We’re at an exciting stage of scale as we build upon our growing market momentum. Our software is trusted by Shell Oil, Genentech, HCA healthcare, Kaiser, Turner, Layton and several others. Join us in bringing AI to construction!
The Role
As a backend engineer at Doxel, you will help define and build the next generation of our project management, commissioning, and field-enablement tools—systems trusted by the world’s largest general contractors and owners delivering mega-projects at unprecedented scale.
You’ll help build and deliver applications that handle massive volumes of complex field data—including videos, images, structured forms, and IoT device outputs—and transform them into fast, intuitive workflows for both office teams and field workers. You’ll architect mobile and web experiences that make capturing, reviewing, and acting on this data effortless in environments where reliability, speed, and clarity matter.
You’ll partner closely with product, design, backend, CV/ML, and platform engineering teams to turn Doxel’s AI and data systems into beautifully executed user experiences. You’ll provide technical leadership end to end shipping 0-1 projects, as well mentoring and coaching across engineering on best practices.
Doxel provides comprehensive health/dental/vision benefits for employees and their families including an Unlimited PTO policy, a 401(k) program, and a flexible work environment among other benefits. Doxel is an equal opportunity employer and actively seeks diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
- Design and developing services and pipelines that support rapid data ingestion, processing, and review at enterprise scale
- Design and develop services that enable realtime collaboration and data-gathering in the field
- Build AI based features that are incorporated into our product
- Collaborate cross-functionally with generalist and specialist engineers, Product, Design, Customer Success, and Operations to deliver seamless endt o-end features
- Managing individual project priorities, deadlines and deliverables
- Successfully launching and optimizing new user-facing features in Doxel’s products
- Contributing to technical planning, feature roadmaps, and long-term architectural decisions for Doxel’s applications ecosystem
- Understanding our customers and championing their priorities
- 8+ years of experience building and shipping backend systems in an SOA and/or EDA environment
- Expertise with modern backend technologies and infrastructure, such as Function as a Service and Infrastructure as Code
- Expertise in data processing and stream technologies
- Expertise in various database and data storage technologies
- Strong familiarity with cloud environments (AWS, GCP, or Azure) and containerized infrastructure
- Experience with data warehousing tools such as Redshift, Snowflake, Databricks, or BigQuery
- Experience with 3D visualization or computer-vision-powered experiences
- Exposure to ML/AI-driven feature development
- Comfort with CI/CD pipelines, observability tooling, and automated testing best practices