Platform Engineer – Senior/Staff/Principal

Job not on LinkedIn

September 20

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Quilter

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Hardware • SaaS • Artificial Intelligence

Quilter is an innovative technology company offering an all-in-one PCB design tool tailored for hardware teams. This platform enables engineers to automate and optimize circuit board layouts, reducing design time from weeks to mere hours. Quilter's software is compatible with existing design tools like Altium and KiCAD, and it imports design constraints to optimize for EMI performance and manufacturing. Offering generative AI-driven design processes, Quilter provides numerous quality design candidates that are production-ready. The company's "Fab for Free" program and open beta version make it a cost-effective choice for electronics companies worldwide.

2 - 10 employees

🔧 Hardware

☁️ SaaS

🤖 Artificial Intelligence

📋 Description

• Build developer-facing tooling, SDKs, and wrappers that abstract away Kubernetes, workflow, and infra details • Design and harden CI/CD pipelines with faster feedback, per-MR preview environments, and reduced flakiness • Deliver dashboards and shared observability: cost, reliability, performance — consumable by engineers and leadership • Partner with engineering teams to codify repeatable workflow patterns into libraries and templates • Play a central role in rebuilding the workflow orchestration platform and design core primitives for AI workloads • Build language-native wrappers and tooling around workflow features to make advanced orchestration accessible • Implement secure-by-default systems: secrets management, auditability, least-privilege defaults, and bastions • Define and enforce SRE practices — incident response, playbooks, SLIs/SLOs, backup/restore automation • Shape the Platform team: standards, processes, and culture that emphasize self-service systems over tickets

🎯 Requirements

• Strong software engineering background — comfortable writing production-quality Python (and ideally Typescript/Go) code • Experience building developer productivity tooling (SDKs, CLI tools, CI/CD pipelines, internal dashboards, preview envs) • Practical Kubernetes fluency — design and debug workloads, tune autoscaling, apply common patterns • Hands-on with Kubernetes and workflow platforms (Argo Workflows, Airflow, Prefect, Temporal, etc.) • Proficient with infrastructure-as-code and containerization — Docker-based services and modern IaC tools (Terraform preferred) • Solid grounding in cloud infrastructure (AWS preferred) — compute, storage, networking, IAM, cost controls • Familiarity with observability stacks (Prometheus, Grafana, OpenCost, Loki/Tempo/OTel) • Comfort operating in high-scale, compute-intensive environments (ML training, batch/parallel workloads) • Bias toward building paved roads and abstractions that make other engineers faster • Prior experience in a Platform or DevProd team at a startup (nice to have) • Background in MLOps foundations — training pipelines, model artifact management, GPU workloads (nice to have) • Familiarity with on-prem or hybrid deployment patterns (nice to have) • Knowledge of compliance frameworks (SOC 2, ISO27001, ITAR, GDPR) and their infra implications (nice to have) • Exposure to multi-tenant SaaS or Bring Your Own Cloud architectures (nice to have) • Contributions to open-source infra/dev-tooling projects (nice to have) • Primarily hiring within the US (occasional exceptions for exceptional talent)

🏖️ Benefits

• Interesting and challenging work • Competitive salary and equity benefits • Health, dental, and vision insurance • Regular team events and offsites (~2x / year) • Unlimited paid time off • Paid parental leave