> Markdown version of [/jobs/ext/4622548-lead-software-engineer-platform](https://www.wearedevelopers.com/jobs/ext/4622548-lead-software-engineer-platform). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Software Engineer, Platform - **Company:** True - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $220,000.0 - $320,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Cloud Computing, Databases, Distributed Systems, Python (Programming Language), Machine Learning, Cloud Services, Machine Learning Operations - **Published:** November 7, 2026 - **Apply:** https://www.juju.com/job/28_25304_30938f779fe95e246fbc3153f062d18b ## About the Role * - At least 5 years of platform or backend engineering experience, including work with distributed systems. * - Strong Python skills, or deep Go or Rust expertise and willingness to work in Python. * - Experience building and scaling infrastructure, task orchestration, and reliable production platforms. * - Application-level engineering experience in addition to infrastructure work. * - Experience with on-call support, cloud infrastructure, and ideally model-serving optimization. * - Background working in a startup or other fast-moving engineering environment, with experience owning systems in production. ## Description Join a platform engineering team at an AI/ML company, building and strengthening the systems that power document processing. You will help ensure customer workloads run quickly and reliably while improving model serving and infrastructure efficiency., * - Own and improve the core platform for document processing workloads, focusing on speed, reliability, and cost efficiency. * - Partner with machine learning teams to serve in-house models efficiently and integrate them into production pipelines. * - Build and maintain databases, task orchestration, workload scheduling, and cloud deployments. * - Improve distributed systems by addressing latency, reliability, and scaling challenges as workload volume grows. * - Join the on-call rotation and take end-to-end responsibility for platform health.