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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Platform Engineer, Security - **Company:** Doxel, Inc. - **Location:** United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Computer Vision, Microsoft Azure, Big Data, Software as a Service, Encodings, Continuous Integration, Data Centers, Data Warehousing, DevOps, Identity and Access Management, Python (Programming Language), Key Management, Object Detection, Reliability Engineering, Web Applications, Three.js, Datadog, Scripting, Google Cloud, Large Language Models, Snowflake, Deep Learning, Containerization, Kubernetes, Low Latency, Terraform, Appdynamics, Data Pipelines, Static Application Security Testing - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/senior-platform-engineer-security-doxel-8615332 ## About the Role * 6+ years in platform engineering, infrastructure/DevOps, or site reliability, with real depth building infrastructure, not just operating it * Strong infrastructure-as-code skills (Terraform) and a track record of replacing ad hoc infra with reusable, self-service patterns * Hands-on cloud depth, ideally Google Cloud (AWS or Azure translates), including IAM, networking, and least-privilege design * Strong experience with Kubernetes and containerized workloads in production. Practical experience embedding security tooling into CI/CD (SAST, SCA, secret scanning, supply chain controls) and building secure-by-default pipelines * Strong programming or scripting ability (Python, Go, or similar) for building platform and automation tooling * A security mindset: you design for least privilege and think about how things get abused, even when security is not the headline of the task * Demonstrated ability to drive platform adoption and influence engineering teams without formal management authority. Preferred * Experience standing up an internal developer platform or paved-road program from scratch * Working knowledge of AI/LLM security risks and a point of view on using AI tools safely * SOC 2, ISO 27001, or similar compliance experience in a fast-moving company. * Experience securing data warehouses or large data pipelines (Snowflake a plus) * Familiarity with construction tech, BIM/3D data, or other domain-rich data products ## Description 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!, As a Senior Platform Engineer, with an emphasis on Security, your main mission is to build out Doxel's internal platform and define the golden paths that engineers rely on, replacing today's hand-rolled infra. Own cloud security posture on GCP, bake security into CI/CD and the supply chain, and help shape how Doxel uses AI safely. What You'll Do * Work with DevOps team to build out golden paths that streamline developer and builder workflows streamlining and applying shift left security policies on CI/CD deployment, internal tooling, LLM, and data science workflows * Own cloud security posture on Google Cloud, landing-zone guardrails, least-privilege IAM, secrets and key management, codified as infrastructure-as-code so secure defaults are baked into golden paths rather than bolted on after * Continuously evaluate attack surfaces across the application, infrastructure, and cloud, prioritize findings by exploitability and blast radius, and feed the highest-leverage fixes back into the platform * Set and enforce AI-usage best practices, guardrails for agentic coding tools internally and Provide a security point of view on product AI/LLM features (prompt injection, data egress, model supply chain), in partnership with engineering leadership * Action on improving security and compliance through a risk based approach implementing SOC2, ISO27001, and ISO27701 security and compliance frameworks. 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