TL;DR: If you:
know infrastructure inside out: Kubernetes, multi-cloud, distributed systems, networking, cybersecurity, and BYOC;
thrive in startups, move fast, and have a relentless drive to execute;
are deeply aligned with our mission to build AI for the physical world;
have a principled but aggressive approach to AI-assisted development…
… you should apply for this role!
About P-1 AI:
At P-1 AI, we are building an AI engineer agent for the physical world named Archie. We maximize Archie’s anthropomorphism so that he fits seamlessly into existing engineering teams and workflows in the form factor of a human engineer. Archie today is at the level of a junior mechanical and electrical engineer, with a quantitative intuition over the product design space and the ability to use complex engineering tools—the same tools his human teammates use. Archie's tech stack includes a custom agentic harness, structured design representation, continual skills learning, and small custom post-trained models (SFT and RLVR) using proprietary semi-synthetic training data sets and environments which create a deep competitive moat. Our ultimate aim is to build engineering ASI. We recently announced a $50 million Series A financing led by NEA, which added former General Electric CEO Jeff Immelt to our board. The round also included the addition of several AI luminaries from Anthropic and Nominal to our existing angel investors from Google and OpenAI.
About the opportunity:
As our dedicated Platform Engineer, you'll own the infrastructure that makes it possible for Archie to operate reliably inside customer environments, evolving our BYOC deployment architecture. You'll tackle hard problems spanning distributed systems, cloud infrastructure, and security, with significant ownership over how Archie is deployed and scaled.
About the role:
Own and evolve the BYOC deployment model for Archie across customer environments, including how systems are distributed, installed, and updated, and how they interact with P-1’s central systems.
Build and own Kubernetes-based infrastructure that runs reliably across multiple clouds and customer setups.
Create deployment tooling using Helm, GitOps, or similar approaches to make installation and operations repeatable.
Implement secure and reliable update and upgrade mechanisms that work even in restricted or locked-down network environments.
Work closely with product, research, and forward-deployed engineers to translate requirements into platform capabilities.
Debug and improve production deployments, identifying bottlenecks in performance, reliability, or operability.
Establish observability, monitoring, and debugging patterns that give us visibility into distributed systems we don’t fully control.
About you:
Have built and operated Kubernetes-based systems in production.
Have designed infrastructure using IaC tools like Terraform, Pulumi, or similar.
Have implemented CI/CD or GitOps workflows that deploy systems across environments.
You are comfortable working across cloud providers (AWS, GCP, Azure) and understand their core primitives.
You have worked on systems that require strong security and networking considerations (e.g., VPCs, identity, encryption).
You like owning problems end-to-end and are comfortable operating in ambiguous, 0-1 environments.
You’re constantly evolving your AI approach for your own technical work.
Location:
Remote (US/Canada) or San Mateo, CA. Remote employees spend one week out of six working together on-site in our San Mateo office. Relocation support available.
Benefits:
Competitive salary, meaningful equity ownership, healthcare, dental, vision, 401(k) match, and unlimited PTO.
Interview process:
Introductory call (30 mins)
Biographical/behavioural interview (45 mins)
Technical interview (60 mins)
CEO interview (30 mins)