Member of Technical Staff, Distributed Systems

Role and Responsibilities

• Design and implement new runtime primitives for our AI platform.
• Build and harden the multi-tenant durable workflow execution system that powers AI-driven physics research at scale.
• Treat our AI platform as a library product.
• Design the programmatic interfaces that researchers and engineers across PSI extend.
• Operate the platform that runs every research workflow and customer-facing AI product at PSI.

What We're Looking For

• Four or more years building and operating distributed systems in production at companies known for engineering rigor (e.g., Google, Netflix, Meta, Cloudflare, Datadog, or comparable).
• You have written code that paying customers, internal teams, or large user bases depend on every day.
• You are fluent in the operational realities of cloud-native infrastructure.
• A track record of designing and shipping a Python library or internal framework that other engineers extend, not just consume.
• You think about API ergonomics, type-driven contracts, composability, and backward-compatible evolution as first-order concerns.
• Real experience implementing or substantially extending orchestration primitives, workflow engines, dataflow systems, or agent runtimes.
• You understand the subtle bugs that come from retries, replays, and non-deterministic execution.
• Operational excellence and architectural judgment.
• You favor simple systems over clever ones, instrument before you optimize, and can explain a programming-model or workflow-engine trade-off in two minutes.

Nice to Have

• Hands-on experience with a durable workflow system such as Temporal, Cadence, Step Functions, Argo Workflows, or Airflow at scale.
• Designed or shipped a DSL, embedded DSL, or authoring surface that compiles to a deployable artifact.
• Production observability built on OpenTelemetry or comparable tooling.

Background

• Background in scientific computing, HPC environments, or research infrastructure.

How We Work

• We are engineering-led. Engineers own problems end-to-end, from spec to ship to on-call.
• We write contracts before logic, test against real systems instead of mocks, and favor simple designs that ship over clever ones that do not.
• Our development process is AI-native: engineers work with agentic coding tools daily, write specs that are legible to humans and agents alike, and lead with leverage.

Location and Compensation

• This role is based in Boston. We will consider remote candidates on a case-by-case basis.
• We offer competitive compensation including salary, benefits, and meaningful early-stage equity.
• We evaluate on technical breadth, systems thinking, scientific curiosity, and shipping velocity.
• We are an equal opportunity employer and value diverse perspectives in building platforms for AI-driven discovery.