As a full stack 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 full-stack 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.
What You'll Do
- 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
What Success Looks Like
- 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
What You Bring
- 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
Preferred
- 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
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