DevOps / Infrastructure Engineer

Architect, provision, and scale the core user agent fleet across a hybrid Railway and AWS ecosystem, ensuring each user retains an isolated, secure, and predictable containerized process with optimized cost tracking and precise lifecycle hooks. •

Establish, manage, and continuously harden private overlay networks using Tailscale in production, linking disparate user agents securely with core Model Context Protocol (MCP) servers and the underlying live trading runtimes. •

Design and construct an end-to-end, zero-touch deployment pipeline utilizing advanced infrastructure-as-code and CI/CD best practices, enabling seamless, single-click automated provisioning of containers, secrets management, and environmental configurations for new users. •

Define, build, and maintain comprehensive monitoring, telemetry, alerting, and automated incident response frameworks to guarantee graceful state retention, preserving live in-flight transaction states across sudden host restarts, scheduled key rotations, or regional cloud outages. •

Oversee system health and participate in direct real-incident response and on-call rotations to maintain strict operational continuity for the live global fleet.

Proven professional experience deploying, monitoring, and scaling complex architectures in production utilizing Railway, or equivalent containerized platform-as-a-service frameworks (such as Fly.io, Render, or Northflank). •

In-depth technical mastery of Amazon Web Services (AWS), with practical expertise spanning Virtual Private Clouds (VPC), Identity & Access Management (IAM), Secrets Manager, and elastic scaling frameworks (ECS / AWS Lambda). •

Demonstrated experience implementing Tailscale within a high-security production environment, with distinct competence configuring Access Control Lists (ACLs), complex subnet routing, and ephemeral node lifecycles. •

Mastery of Docker containerization, comprehensive CI/CD deployment pipelines, and modern Infrastructure-as-Code (IaC) paradigms. •

Technical familiarity with blockchain mechanics, smart contract interactions, or web3 infrastructure paradigms to support decentralized application layers. •

A proven professional history managing environments where system stability impacts critical financial outcomes, paired with total comfort managing on-call duties and live incident response.

• Direct experience deploying, managing, and monitoring Large Language Model (LLM) or autonomous AI agent fleets at multi-tenant scale. • Prior exposure to quantitative trading systems, high-frequency execution runtimes, or deep integrations with platforms such as Hyperliquid.

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