DevOps / Infrastructure Engineer

Mlabs Ltd
United States
2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$100,000.0 - $130,000.0
Working hours
Regular working hours
Job source

Tech stack

Access Control List Amazon Web Services Application Layers Continuous Integration DevOps Identity and Access Management Subnetting Key Management Network Security Platform as a Service (PAAS) Blockchain User Provisioning Software
+8 more
Delivery Pipeline Large Language Models AWS Lambda Amazon Virtual Private Cloud (VPC) Web3.js Virtual Agents Virtual Private Clouds Docker

Job description

We are hiring on behalf of our client who is seeking an exceptional, production-proven Infrastructure & DevOps Engineer to take absolute ownership of the deployment, secure networking, architectural lifecycle, and overall reliability of this distributed agent fleet from day one. The client is engineering a sophisticated infrastructure designed to launch a highly distributed fleet of managed, single-tenant personal artificial intelligence (AI) trading agents. Operating non-stop, these isolated processes execute high-frequency, complex financial workflows natively on blockchain infrastructure, dedicated exclusively to individual user portfolios., * Fleet Orchestration & Scaling: 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.

  • Secure Network Engineering: 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.
  • Automated User Provisioning: 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.
  • Operational Resilience & SRE: 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.
  • Incident Management: Oversee system health and participate in direct real-incident response and on-call rotations to maintain strict operational continuity for the live global fleet.

Requirements

Do you have experience in Virtual Private Clouds?, * Container PaaS Orchestration: 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).

  • Advanced AWS Proficiency: 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).
  • Production-Grade Tailscale Networking: 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.
  • Modern Infrastructure & CI/CD: Mastery of Docker containerization, comprehensive CI/CD deployment pipelines, and modern Infrastructure-as-Code (IaC) paradigms.
  • Blockchain & Onchain Context: Technical familiarity with blockchain mechanics, smart contract interactions, or web3 infrastructure paradigms to support decentralized application layers.
  • High-Availability / Financial SRE Background: 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.

Nice to Have

  • 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.

Benefits & conditions

  • Highly competitive compensation package
  • The flexibility of a fully remote operating environment with an immediate start timeline.
  • The opportunity to shape the architectural foundation of a cutting-edge technical ecosystem intersecting Artificial Intelligence and decentralized financial infrastructure.
  • Access to top-tier modern tooling, modern infrastructure frameworks, and a highly streamlined, zero-red-tape development culture.

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