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AI Summary

Design, build, and ship end-to-end features using React, TypeScript, and Python or Node.js services. Integrate AI-native capabilities and automate internal engineering workflows while maintaining high security standards.

We are looking for a full stack developer who is comfortable owning a feature from the database schema to the last pixel and who already builds with AI as a core part of how they work, not as a novelty. You will build the platforms our security researchers use to run engagements, the products our clients use to consume findings, and the AI-assisted workflows that let a small team operate at a scale that should not be possible. The work is real product engineering against real adversarial conditions, and the security bar is high because our customers are the reason it has to be.

Responsibilities

  • Design, build, and ship features end to end across a React and TypeScript front end and Python or Node.js services, taking ownership from technical design through production support.
  • Model data and design APIs that hold up as requirements change — clear contracts, sane migrations, and schemas that will not need to be rescued in six months.
  • Build AI-native product capabilities: LLM orchestration, agentic and multi-step workflows, retrieval over engagement data, and structured output that downstream systems can rely on.
  • Use AI coding tooling aggressively in your own development loop while maintaining the review discipline that keeps generated code from becoming a liability.
  • Automate internal engineering and security workflows, turning processes our researchers currently run by hand into durable product surface.
  • Write secure code by default — input validation, authentication and authorization, secrets handling, dependency hygiene — and treat security review as part of shipping, not a gate at the end.
  • Participate in code review as both author and reviewer, raising the standard of the codebase rather than just approving diffs.
  • Deploy and operate what you build: containerized services, cloud infrastructure, CI/CD pipelines, monitoring, and the on-call ownership that comes with running production systems.
  • Collaborate directly with security researchers, auditors, and product stakeholders to translate deep domain expertise into software that non-experts can use.
  • Contribute to technical direction — framework choices, architecture, and the tradeoffs behind them — and document decisions so the team can move without you in the room.

Qualifications

  • 4 or more years building and shipping production web applications, with genuine ownership on both the front end and the back end.
  • Strong React and TypeScript, including modern state management, component architecture, and CSS competent enough to build an interface without a designer hovering.
  • Strong server-side skills in Python, Node.js, or both, with production experience designing REST or GraphQL APIs.
  • Solid relational database experience — PostgreSQL preferred — including schema design, query performance, and migrations.
  • Experience with cloud infrastructure (AWS, GCP, or Azure), Docker, and CI/CD pipelines you configured yourself.
  • Demonstrated AI-forward development practice: you integrate LLM APIs into real products, you use AI coding assistants as part of your daily loop, and you can articulate where they accelerate you and where they need a human.
  • Security-minded engineering instincts and a working understanding of common web vulnerability classes and how to prevent them.
  • Excellent asynchronous written communication and the self-direction to own outcomes across time zones without being managed day to day.
  • Comfort operating in ambiguity in a constantly changing and evolving work environment where growth is non-stop.
  • Willingness to learn the technical aspects of blockchain and cybersecurity.

Bonus Points

  • Web3 development experience — ethers.js or viem, wallet integrations, RPC providers, or Solidity and Rust smart contract familiarity.
  • Experience building agentic systems, working with the Model Context Protocol, vector databases, or evaluation frameworks for LLM features.
  • DevSecOps experience: infrastructure as code, secrets management, supply chain security, or automated security scanning in CI.
  • Prior work at a cybersecurity, fintech, or crypto company, or on products handling sensitive customer data.
  • Experience taking a product from zero to one on a small team.
  • Open source contributions.
  • Knowledgeable of the latest trends in Blockchain and DeFi.

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