Member of Technical Staff
- New York, NY or Boulder, CO
- Senior hire: $250K–$400K+Junior hire: $200K–$300K
- Early-stage equity
- Comprehensive health, dental & vision, One Medical membership, daily lunch & gym membership
Email careers@plasma.ai
About Plasma
AI is crossing a threshold. Systems of agents are beginning to do consequential work unattended, for hours at a time. Plasma builds what those systems need: durable memory, shared context, budgets and approvals, and a record of everything that happens — the infrastructure that makes autonomous organizations trustworthy at scale.
The Opportunity
We're looking for a founding-level platform engineer to work alongside our CTO on Plasma's core infrastructure. You'll build the data pipelines, agent orchestration layers, API infrastructure, and reliability foundations that everything else runs on.
We're looking for a commercially minded, product-oriented engineer from a top AI lab or quantitative finance background. If you've spent time somewhere where the bar for production systems is unusually high and want to build something from scratch, this role is for you.
What You'll Work On
Core Platform — Own the infrastructure (compute, storage, APIs, pipelines) Plasma's systems run on. Architectural decisions you make early will compound for a long time
Agent Infrastructure — Build the orchestration, observability, and governance controls that let AI agents operate reliably in production
Data Systems — Design scalable pipelines where correctness and auditability are requirements, not nice-to-haves
Reliability & Observability — Establish the monitoring, alerting, and incident response practices that make Plasma's systems dependable
Technical Bar — Set the standard for engineering quality and shape architectural decisions
What We're Looking For
Deep expertise in distributed systems, backend infrastructure, or data engineering
Experience building and operating data-intensive systems in production (pipelines, streaming, warehouses, enterprise orchestration, model serving)
Familiarity with AI/ML infrastructure — LLM systems, agent frameworks
Comfort with cloud infrastructure (AWS, GCP), modern DevOps practices, and large-scale enterprise integrations
Background at an AI lab, top quantitative firm, or high-rigor infrastructure team is a strong plus
Exceptional judgment about when to build, when to buy, and when to keep it simple