Member of Technical Staff, Security

Overview

Physical Superintelligence is a stealth startup with roots at Google, Harvard, Meta, MIT, Oxford, Johns Hopkins, Cambridge, and the Perimeter Institute building AI systems to discover new physics at scale. We are seeking engineers to build platform infrastructure at the intersection of computational science, AI systems, and software engineering.

Our mission is to discover and commercialize transformative physics breakthroughs at scale with artificial superintelligence, safely, verifiably, and for broad public benefit.

The last century's golden age of physics gave us transistors, lasers, and nuclear energy. We believe artificial superintelligence will unlock the next one. We're creating the infrastructure to industrialize scientific discovery and usher in this new era.

We have one product: new physics, at scale.

Role and Responsibilities

• Own end-to-end security strategy for PSI. Architect security into our AI platform, paid API, and enterprise customer engagements before they ship, not after. Application security, cloud security, identity and access management, secrets management, audit logging, and detection and response are yours to design and run.

• Lead SOC2 readiness and, at the right time, additional compliance programs such as ISO 27001 and customer-specific security questionnaires. Translate compliance requirements into engineering controls that engineers actually adopt, not paperwork that slows the team.

• Set the security bar in architecture and design reviews across the AI platform. Threat-model new runtimes, agent integrations, multi-tenant isolation, model-provider risk, training-data integrity, and customer-facing surfaces. Decide which risks are acceptable and which are not, with explicit reasoning the rest of the engineering team can trust.

• Build and lead the security function as PSI scales. Operate as the single technical security voice today; hire and grow a small high-leverage team over the next 18 months. Own incident response, third-party and model-provider risk, and the security relationship with enterprise customers in physics, energy, and adjacent verticals.

What We're Looking For

• Ten or more years in security engineering at scale, with a track record at companies known for security maturity (e.g., Google, Stripe, Cloudflare, Anthropic, Microsoft, Apple, Snowflake, Databricks, Palantir, or comparable). You have built security functions, not just contributed to them.

• Deep technical fluency across application security, cloud security on GCP, AWS, or Azure, identity and access management, and DevSecOps in Kubernetes-native environments. You read code, write Python for security tooling, and architect controls that engineers willingly adopt.

• Hands-on experience leading SOC2 or ISO 27001 readiness at a scaling company, owning the program from gap analysis through attestation. You know how to translate compliance language into engineering reality without slowing shipping velocity.

• Demonstrated ability to set strategy and operate without bureaucracy. You have been a founding or near-founding security hire at a fast-growing company; you have built threat models, incident response runbooks, and a small high-leverage team without becoming a process department.

Nice to Have

• Background in AI and ML security: model weights protection, prompt injection defense, agent supply chain, training data integrity, red teaming for LLMs.

• Public security research, conference talks at top venues (Black Hat, DEF CON, USENIX Security), CVE discovery, or substantial open-source security contributions.

• Experience designing multi-tenant isolation and security architecture in agentic systems, research platforms, or scientific computing infrastructure.

• Government clearance, classified-program background, or experience protecting IP-bearing scientific or research environments.

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 is an in-person role based in Boston or San Francisco. 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.