Staff Software Engineer
Boon Technologies, Inc. · Full-time · Posted 2w ago
Boon is the professional AI platform built specifically for construction. Founded in the San Francisco Bay Area in 2023 by product and engineering leaders from Samsara, Apple, Google and DoorDash. Boon is backed by leading Silicon Valley venture capitalists.
Our AI agents embed directly into existing workflows, from preconstruction estimating to bid management. They automate the repetitive tasks that drain time and margins while surfacing the insights leaders need to make faster and more confident decisions.
The result is measurable impact. Teams move faster, bids are submitted sooner, win rates increase, and costs are reduced. Boon enables construction companies to build more, generate more revenue, and grow with confidence.
Boon AI is building the agentic operating system for construction preconstruction — the layer that reads blueprints, specs, and bid documents, and does the estimator's work with them. Our platform spans a Rails product monolith, Python computer-vision services (DINOv3/SAM-class vision models reading drawings), an LLM agent runtime orchestrating multi-step construction workflows, and a model/eval infrastructure that keeps accuracy honest. We're live with GCs and subs across the country, shipping daily, and scaling from thousands to hundreds of thousands of drawings per month. The Staff Software Engineer sits across every one of those surfaces and makes sure the system we're building this quarter is the system we can still build on three years from now.
Own the end-to-end technical architecture across the Rails product app, Python ML/CV services, agent SDK layer, and data platform — including the hard tradeoffs between enterprise customer requirements and shipping speed
Drive scalability, reliability, and cost architecture of our computer vision/LLM/VLM inference pipelines as we scale blueprint throughput by 100×
Set the technical direction for our model infrastructure — vision models, LLM orchestration, agent runtime, MLflow registry, eval harnesses, and GPU budget
Lead architectural review, raise the engineering bar through code review and design docs, and lead decisions considering cross-system tradeoffs
Mentor senior and junior engineers. Prior engineering management experience a bonus.
Partner with the CEO and product on the 12–18 month technical roadmap: what we build in-house, what we buy, what we deprecate, and when to invest in platform vs. features
Still write code — this is a working architect role; you'll be in incident response, PR review, and the hardest technical problems on a weekly basis
You've shipped production systems that handle messy real-world input — documents, PDFs, images, OCR, user-generated chaos — not just clean API-to-API services
You have strong opinions on monolith vs. services, model-in-the-loop UX, when to add complexity, and when "just add another microservice" is the wrong answer
You've built or deeply operated computer vision or LLM/agent systems in production, and you understand eval infrastructure as a first-class engineering discipline
You move fast without breaking the foundations — comfortable shipping daily, comfortable saying "stop, we need to rebuild this part" and similarly “stop, we should NOT reinvent the wheel and use battle-tested open-source/paid solutions”
You thrive in flat, direct, high-velocity teams where the architect sets the technical path and defends it with code and data, not slides
Bonus: construction, AEC, or other vertical-SaaS experience; or you've taken a company from Series A to C technically
Culturally, you embody working as “one team” and strive to “get things done”, instead of passing the buck around
8+ years of experience building production software, with a track record of delivering in fast-paced, high-growth environments
Deep experience with at least two of: large Rails or Python monoliths, computer vision pipelines in production, LLM / agent systems at scale, data-intensive B2B SaaS
Hands-on fluency with cloud infrastructure (AWS and/or GCP), PostgreSQL at scale, background job systems (RabbitMQ, SideKiq), and modern deployment practices
Track record of leading architectural decisions that held up under 10×+ growth
Has written and shipped production code in the last 6 months — and plans to keep doing so
Familiar with some SRE (Service Reliability) and DevOps - Kubernetes, Helm, CI/CD and ability to drive and collaborate with Boon’s dedicated SRE teammates.
At Boon, we want to attract and retain the best employees and compensate them in a way that appropriately and fairly values their individual contribution to the company. With that in mind, we carefully consider a number of factors to determine the appropriate starting pay for an employee, including their primary work location and an assessment of a candidate’s skills and experience, as well as market demands and internal parity. This estimate can vary based on the above mentioned factors, so the actual starting annual base salary may be above or below this range. A Boon employee may be eligible for additional forms of compensation, depending on their role, including sales incentives, discretionary bonuses, and/or equity in the company.
As an equal-opportunity employer, Boon is committed to providing employment opportunities to all individuals. All applicants for positions at Boon will be treated without regard to race, color, ethnicity, religion, sex, gender, gender identity and expression, sexual orientation, national origin, disability, age, marital status, veteran status, pregnancy, or any other basis prohibited by applicable law.
New Zealand