
Quilter
Quilter builds AI-powered software that automates printed circuit board (PCB) layout from circuit schematics into fab-ready designs for electronics and hardware engineering teams. It sells enterprise software that lets engineers generate and validate multiple board variants quickly, integrating physics checks to reduce redesigns. Founded in 2019 and headquartered in Los Angeles, the company is privately held.
Open Positions at Quilter
7 open positions
Quilter is seeking a Senior/Staff Platform Engineer to build and operate secure cloud infrastructure supporting compute-intensive PCB design workloads and customer-managed deployments. The role centers on cloud security, infrastructure maintenance, compliance automation, recovery, and operational reliability.
Lead customer-facing enterprise deployments and integrations of Quilter’s AI-powered PCB design platform. You’ll combine Kubernetes, cloud infrastructure, identity integration, troubleshooting, and automation to make customer-managed deployments reliable and repeatable.
Build Python-based PCB/CAD integrations that turn customer blockers into production fixes, features, and more reliable workflows. You’ll work closely with customers and go-to-market teams while developing LLM- and agent-assisted investigation tooling.
Build the integrations that connect Quilter’s PCB automation platform with leading CAD tools, working primarily in Python on complex file formats and internal board representations. You’ll also develop AI-powered reverse-engineering workflows and gain deep experience with coding agents, evaluations, and MCP server design.
Build the production infrastructure powering Quilter’s automated PCB component-placement ML system. You’ll own training, data, experimentation, serving, monitoring, and architectural systems across a fully distributed research-focused team.
Join Quilter’s distributed Placer Team to build GPU-accelerated machine-learning systems that automate PCB component placement. You’ll span research through production while tackling optimization, geometric deep learning, and a challenging real-world combinatorial problem.
Build the next generation of automated PCB design through high-performance C++ algorithms, scalable systems, and physics-aware simulations. You’ll help shape technical direction while tackling computational geometry, optimization, routing, and high-performance computing challenges.