Full Stack Software Engineer - (Hybrid/Seattle)

Forest Vision•Seattle, WA

13h•Hybrid

About The Position

ForestVision.ai is building the AI layer for the global timber industry, which currently relies on outdated methods for log load management, leading to significant estimation errors. The company is replacing these methods with patented multimodal computer vision and AI agents deployed at truck scales. Unlike competitors using consumer smartphones, ForestVision.ai uses industrial-grade camera rigs and edge-computing boxes for high-throughput mill entryways. Their solution generates a state-certified audit trail, transforming raw pixels into deterministic, industry-standard measurements. The Full Stack Software Engineer will contribute to the full-stack development of edge computing, kiosk, and pipeline infrastructure, focusing on log reconstruction and cloud scaling. They will also engineer internal operational and monitoring systems for development, troubleshooting, and system performance, and help build customer-facing SaaS products like contract management and reporting tools.

Requirements

5+ years of professional software engineering experience.
Strong full-stack engineering skills with React, Next.js, TypeScript, and Node.js.
Strong AWS experience, especially with scalable cloud systems.
Interest in computer vision, model training, data pipelines, or applied AI systems.
Must embrace AI and effectively use AI to solve problems.
Experience building production applications from frontend through backend.
Comfortable debugging distributed systems, cloud workflows, and data processing issues.
Able to work effectively in an existing codebase and take ownership of scoped projects.

Nice To Haves

Experience scaling image processing, ML, geospatial, or data-heavy systems.
Familiarity with CI/CD, observability, and production support.

Responsibilities

Build end-to-end web and mobile app experiences using React, Next.js, and AWS.
Develop reliable product features across frontend, backend, data, and cloud infrastructure.
Help scale distributed systems that support large image datasets and vision workflows.
Build and improve tools for vision model training, evaluation, and operational monitoring.
Design backend workflows that can process complex, high-volume vision pipeline jobs.
Effectively use AI tools to solve problems, improve productivity, and accelerate development.
Improve system reliability, performance, and observability as usage grows.
Work closely with product and technical stakeholders to turn ambiguous needs into working software.
Write clean, maintainable code and tests that support long-term product quality.