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Member of Technical Staff

  • LocationNew York, NY or Boulder, CO
  • SalarySenior hire: $250K–$400K+Junior hire: $200K–$300K
  • EquityEarly-stage equity
  • BenefitsComprehensive 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 PlatformOwn the infrastructure (compute, storage, APIs, pipelines) Plasma's systems run on. Architectural decisions you make early will compound for a long time

  • Agent InfrastructureBuild the orchestration, observability, and governance controls that let AI agents operate reliably in production

  • Data SystemsDesign scalable pipelines where correctness and auditability are requirements, not nice-to-haves

  • Reliability & ObservabilityEstablish the monitoring, alerting, and incident response practices that make Plasma's systems dependable

  • Technical BarSet 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