Quilter
Platform Engineer (Senior, Staff, or Principal level)
Quilter, Los Angeles, California, United States, 90079
Platform Engineer (Senior, Staff, or Principal level)
At Quilter, we are helping electrical engineers save time and accomplish more by automating the tedious and time‑consuming task of designing printed circuit boards (PCBs). Our small team is composed of experts in electrical engineering, electromagnetic simulation, ML/AI, and high‑performance computing (HPC). We are inventing and leveraging novel techniques to solve the decades‑old problem of automating circuit board design where today hundreds of billions of dollars are spent. We have raised $25 million in Series B funding from some of the very best and are charging full‑speed toward our goal.
Our values:
Focus on the mission ,
Build great things that help humans ,
Demonstrate grit ,
Never stop learning ,
Pursue excellence .
What You’ll Do
Build developer‑facing tooling, SDKs, and wrappers that abstract away Kubernetes, workflow, and infra details so engineers can compose and run secure cloud processes without becoming infra experts.
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 our workflow orchestration platform, helping design core primitives and abstractions that power Quilter’s AI workloads.
Build language‑native wrappers and tooling around workflow features, making advanced orchestration accessible as simple SDK calls.
Implement secure by default systems: secrets management, auditability, least‑privilege defaults, and bastions.
Help define and enforce SRE practices — incident response, playbooks, SLIs/SLOs, backup/restore automation.
Shape the foundation of the Platform team itself: standards, processes, and culture that emphasize self‑service systems over tickets.
What We’re Looking For
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 — able to design and debug workloads, tune autoscaling and apply common patterns without needing deep internals expertise.
Hands‑on with Kubernetes + workflow platforms (Argo Workflows, Airflow, Prefect, Temporal, etc.).
Proficient with infrastructure‑as‑code and containerization — design and maintain Docker services and manage infra with 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 (e.g., ML training, batch/parallel workloads).
Bias toward building paved roads and abstractions that make other engineers faster.
Nice to Have
Prior experience in a Platform or DevProd team at a startup.
Background in ML Ops foundations—training pipelines, model artifact management, GPU workloads.
Familiarity with on‑prem or hybrid deployment patterns (networking, packaging, observability bundles).
Knowledge of compliance frameworks (SOC 2, ISO27001, ITAR, GDPR) and how they affect infra decisions.
Exposure to multi‑tenant SaaS or Bring Your Own Cloud architectures.
Contributions to open‑source infra/dev‑tooling projects.
Please note : We are an equal‑opportunity employer. At this time, we are focused on hiring primarily within the US, with occasional exception to accommodate exceptional talent.
What We Offer
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
#J-18808-Ljbffr
Our values:
Focus on the mission ,
Build great things that help humans ,
Demonstrate grit ,
Never stop learning ,
Pursue excellence .
What You’ll Do
Build developer‑facing tooling, SDKs, and wrappers that abstract away Kubernetes, workflow, and infra details so engineers can compose and run secure cloud processes without becoming infra experts.
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 our workflow orchestration platform, helping design core primitives and abstractions that power Quilter’s AI workloads.
Build language‑native wrappers and tooling around workflow features, making advanced orchestration accessible as simple SDK calls.
Implement secure by default systems: secrets management, auditability, least‑privilege defaults, and bastions.
Help define and enforce SRE practices — incident response, playbooks, SLIs/SLOs, backup/restore automation.
Shape the foundation of the Platform team itself: standards, processes, and culture that emphasize self‑service systems over tickets.
What We’re Looking For
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 — able to design and debug workloads, tune autoscaling and apply common patterns without needing deep internals expertise.
Hands‑on with Kubernetes + workflow platforms (Argo Workflows, Airflow, Prefect, Temporal, etc.).
Proficient with infrastructure‑as‑code and containerization — design and maintain Docker services and manage infra with 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 (e.g., ML training, batch/parallel workloads).
Bias toward building paved roads and abstractions that make other engineers faster.
Nice to Have
Prior experience in a Platform or DevProd team at a startup.
Background in ML Ops foundations—training pipelines, model artifact management, GPU workloads.
Familiarity with on‑prem or hybrid deployment patterns (networking, packaging, observability bundles).
Knowledge of compliance frameworks (SOC 2, ISO27001, ITAR, GDPR) and how they affect infra decisions.
Exposure to multi‑tenant SaaS or Bring Your Own Cloud architectures.
Contributions to open‑source infra/dev‑tooling projects.
Please note : We are an equal‑opportunity employer. At this time, we are focused on hiring primarily within the US, with occasional exception to accommodate exceptional talent.
What We Offer
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
#J-18808-Ljbffr