Paradigm Logo

Paradigm

Infrastructure Engineer, Applied AI

Posted One Month Ago
In-Office
San Francisco, CA, USA
250K-400K Annually
Mid level
In-Office
San Francisco, CA, USA
250K-400K Annually
Mid level
Build and operate the core control plane and durable services coordinating agent runs; develop and harden a sandboxed Kubernetes runtime; manage secrets and secure egress; own reliability, monitoring, incident response, and failure recovery; and maintain self-hosted deployment, configuration, and upgrades for Centaur.
The summary above was generated by AI

INFRASTRUCTURE ENGINEER, APPLIED AI

The Firm

Paradigm is a San Francisco-based investment firm focused on frontier technologies across the globe, with over $11 billion in assets under management. We make investments in companies and protocols at all stages, ranging from early-stage venture financing rounds to growth equity to liquid assets.

Paradigm was co-founded in 2018 and is co-led by Matt Huang and Alana Palmedo. We’ve been hard at work investigating the world’s most beautiful technical problems since day one. Our research-driven approach helps us build relationships with founders and entrepreneurs, but it also reflects our broader goal of accelerating the progress of frontier technology.

The Role

Over the last eight years Paradigm has built some of the most used open-source software in the crypto industry, including Reth and Foundry. Earlier this year we published EVMBench with OpenAI, launched Optimization Arena and hosted the Auto Research hackathon. More recently, we open-sourced Centaur, a self-hosted runtime for multiplayer AI agents, which we’ve been using to transform how we work at Paradigm and Tempo.

All of these were done part-time by people on Paradigm’s Investing & Research team. This has made us realize that we are people-bound, not idea or impact bound. We need to grow our team to achieve our ambitions.

We want to do three things:

  1. Experiment aggressively. We will push the capabilities of models, harnesses and infrastructure to the limit in service of Paradigm’s broader goals in investing, research, and building.

  2. Build in public. We will get our hands dirty building useful open-source products.

  3. Invest. We will leverage our infrastructure - an area we think is still ripe for disruption with AI - to be better investors. By understanding infrastructure gaps experientially, we may incubate companies that will accrue value by addressing these gaps.

As we deploy more long-running agentic capabilities, we may get into fundamental research, forecasting, model cost optimizations etc., but that is not our focus yet.

We are looking for fearless engineers for this project who understand infrastructure, security, AI models, harnesses, and Slackbots. You will work directly with Georgios, Arjun, Matt Slipper, and the broader Paradigm team, alongside Tempo, and other companies that are themselves operating at the frontier.

Your work will directly impact how Paradigm operates every day. If this sounds like you, reach out.

Responsibilities

  • Control plane and durability: Own the core services that coordinate agent runs, keeping execution state durable and recoverable through restarts, failovers, and everything that goes wrong in production.

  • Execution runtime: Build and harden the sandboxed, Kubernetes-based runtime that isolates agent sessions, covering provisioning, lifecycle, and the network controls that make untrusted agent code safe to run.

  • Secrets and secure egress: Maintain the credential model that lets agents call third-party APIs without ever holding raw keys.

  • Reliability and observability: Own monitoring, alerting, incident response, and the failure-recovery behavior the system relies on.

  • Self-hosted deployment: Keep Centaur something any organization can run inside its own walls, with clean deployment, sane configuration, and painless upgrades.

Qualifications and Experience

  • A track record of building world-class products

  • Experience applying modern AI and software systems to solve complex, ambiguous problems end-to-end

  • Comfortable navigating everything from foundational models to full-stack product delivery

  • Pragmatic, product-minded builder who cares about solving real problems rather than overfitting to academic ML goals

  • Ability to work autonomously and as a collaborator on the team

Attributes

  • Exceptional team player

  • Extreme open-mindedness

  • Clarity of thought

  • Clear and concise communication (both written and verbal)

  • Technical depth; analytical; rigorous

  • Highly curious; fast learner

  • Ability to bridge technical and investing mindsets

  • Interest in frontier technologies and crypto markets

Similar Jobs

One Month Ago
In-Office
Mountain View, CA, USA
194K-352K Annually
Mid level
194K-352K Annually
Mid level
Artificial Intelligence • Automotive • Information Technology • Robotics
Design and build safe, auditable agent and autoresearch infrastructure: closed-loop evaluation, isolation and permissioning, experiment orchestration, and large-scale inference/training pipelines. Enable autonomous research loops, evaluator and confidence machinery, and agent runtime features (orchestration, sandboxing, tool frameworks, memory, retrieval). Work end-to-end with engineers to deploy trustworthy LLM-agent capabilities against production systems.
Top Skills: Attention MechanismBatchingC++Cloud InfrastructureContext HandlingData PipelinesDistillationDistributed SystemsEvaluation PipelinesExperiment OrchestrationGoHyperparameter SearchInference ServingIsolationKv-CacheLarge Language Models (Llms)Memory SystemsModel RoutingObservabilityOrchestrationPlugin/Skill FrameworksPreference OptimizationPrefix CachingPythonQuantizationQueuingReinforcement Learning (Rl)Retrieval SystemsRustSandboxingSecurity IsolationSpeculative DecodingStorageSupervised Fine-Tuning (Sft)Tool Integration
34 Minutes Ago
In-Office
Sunnyvale, CA, USA
182K-242K Annually
Senior level
182K-242K Annually
Senior level
Cloud • Information Technology • Machine Learning
Lead the marimo engineering team across its open-source Python notebook ecosystem and molab cloud service. Manage and mentor engineers, guide architecture and technical direction, oversee staffing and releases, improve testing and CI/CD, and establish reliable production operations including observability, incident response, and capacity planning. The role also involves evaluating community contributions, translating user feedback into product improvements, and strengthening engineering practices as the team grows.
Top Skills: APIsAutomated TestingCi/CdGrafanaKubernetesObservability SystemsPrometheusPython
46 Minutes Ago
Hybrid
Santa Clara, CA, USA
167K-291K Annually
Senior level
167K-291K Annually
Senior level
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
Architects and operates enterprise cryptographic security services for a multi-tenant SaaS platform. Responsibilities include certificate lifecycle management, key management, secrets distribution, PKI, Kubernetes deployment, threat modeling, incident response, compliance with FIPS and regulated-environment requirements, and evaluating AI/ML for security applications. The role also mentors engineers, collaborates across product and security teams, and advances post-quantum cryptography readiness.
Top Skills: Ci/CdFipsGoHelmHsmJavaKmsKubernetesPkiTls

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account