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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Technical Architect - **Company:** BOON AI INC. - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $115,000.0 - $135,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Systems Engineering, Computer Vision, Software as a Service, Cloud Computing, Code Review, Databases, Continuous Integration, Data Infrastructure, Software Design Documents, DevOps, Python (Programming Language), PostgreSQL, Machine Learning, Open Source Technology, RabbitMQ, Inference Optimization, Systems Integration, Virtualization Technology, Web Services, Cloud Platform System, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Agentic-AI, Kubernetes, Information Technology, Production Code, Machine Learning Operations, Data Pipelines - **Published:** October 14, 2026 - **Apply:** https://www.builtincolorado.com/job/technical-architect/11700136?handler=ApplyRedirect ## About the Role * 10+ years building production software; 3+ years as senior staff, principal, architect, or CTO at a product company * 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. ## Description Be an Early Applicant Remote Hiring Remotely in United States Expert/Leader Remote Hiring Remotely in United States Expert/Leader Owns end-to-end technical architecture across Rails, Python machine-learning services, agent infrastructure, and data platforms. Leads scalability, reliability, cost optimization, model infrastructure, architectural reviews, technical roadmap decisions, incident response, code reviews, and engineering mentorship. The role remains hands-on, requiring production coding and expertise in computer vision, LLM systems, cloud infrastructure, databases, background jobs, Kubernetes, and DevOps practices. The summary above was generated by AI About Boon 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. About the Role 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 Technical Architect 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. In this role, you will: * 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 mentor senior engineers on cross-system tradeoffs * 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, Architect and deploy production-grade autonomous AI agents for semiconductor manufacturing. Responsibilities include designing multi-agent systems, RAG and agent pipelines, evaluation and profiling frameworks, MCP/A2A integrations, security controls, and Kubernetes-based CI/CD deployments. The role requires optimizing inference workloads, transforming AI prototypes into scalable systems, collaborating with data teams and manufacturing experts, and mentoring engineers. Top Skills: A2AAgent-To-Agent ProtocolAgentic AiCi/CdCloud ComputingComputer VisionCrewaiDockerFunction CallingGenerative AiGoogle Agent Development KitKubernetesLangchainLanggraphLangsmithLarge Language ModelsMcpMicrosoft Agent FrameworkModel Context ProtocolOpentelemetryPrompt EngineeringPythonPyTorchPytorch ProfilerRagRustScikit-LearnSignal ProcessingTensorFlowTensorrt-LlmTypescriptVector SearchVllm, Micron Technology, Architect and deploy autonomous Agentic AI systems for semiconductor manufacturing. Responsibilities include developing multi-step AI agents, integrating LLMs with enterprise tools, building RAG and multi-agent pipelines, evaluating and profiling agent performance, deploying workloads through CI/CD to Kubernetes and cloud environments, implementing security controls, and mentoring engineers. The role requires production-scale AI, data pipeline, inference optimization, and systems engineering expertise. Top Skills: Agent-To-Agent ProtocolCi/CdCloud ComputingCrewaiDockerGoogle Agent Development KitKubernetesLangchainLanggraphLangsmithLarge Language ModelsMicrosoft Agent FrameworkModel Context ProtocolOpentelemetryPythonPyTorchRetrieval-Augmented GenerationRustScikit-LearnTensorFlowTensorrt-LlmTypescriptVector SearchVllm, LogicMonitor