Location: Based in US to GMT timezones

Remote | Full-time

Compensation: $120K - $150K

A confidential client operating at the intersection of decentralized finance and artificial intelligence is seeking a Senior DevOps / SRE Engineer. Our client develops sophisticated infrastructure for autonomous AI trading agents on the Hyperliquid network. This role is critical to the organization’s mission: managing high-stakes environments where infrastructure reliability directly impacts capital protection.

The successful candidate will own the architecture that keeps dozens of concurrent AI agents alive, fast, and secure. Unlike traditional web applications where downtime results in a 404 error, downtime in this environment means open financial positions are left unprotected. This is a high-impact position designed for an engineer who thrives on building resilient, zero-downtime systems for autonomous agents managing real-time financial workloads.

Key Responsibilities

• Agent Infrastructure Management: Build and maintain the infrastructure for concurrent AI trading agents, managing complex cron schedules, state files, and trailing stop processes.
• Deployment & Orchestration: Deploy and manage agent environments, including workspace persistence, isolated session management, and Model Context Protocol (MCP) server connectivity.
• CI/CD Pipeline Development: Design and operate pipelines for shipping trading skills and plugins to production without interrupting live trading activity.
• Zero-Downtime Operations: Execute deployment strategies (blue/green, canary) ensuring active financial positions remain protected during every infrastructure change.
• Observability & Monitoring: Build comprehensive alerting across the full stack using metrics, logs, and traces to detect agent failures, state file corruption, or infrastructure regressions before financial loss occurs.
• Cloud & Database Scaling: Operate and scale core platform infrastructure, including Kubernetes (EKS) clusters, Redis, Postgres, ClickHouse, and Kafka.
• Blockchain Reliability: Maintain blockchain node infrastructure and ensure stable connectivity to exchange APIs and on-chain transaction systems.
• Incident Leadership: Lead incident response and on-call practices, including debugging, mitigation, and post-mortems to improve long-term platform reliability.

Requirements

• Professional Experience: Extensive experience in DevOps, SRE, or Infrastructure Engineering, preferably within a startup environment where systems were built from the ground up.
• Kubernetes Expertise: Proven track record of deploying, scaling, and debugging production workloads, specifically within AWS EKS.
• Infrastructure as Code (IaC): Proficiency with tools such as Terraform, Ansible, or equivalent frameworks.
• Containerization: Hands-on experience with Docker and Helm for packaging production services.
• Data Systems: Experience operating production-grade data and messaging systems (Redis, Postgres/RDS, ClickHouse, Kafka).
• Observability Tooling: Strong experience with Prometheus, Grafana, Datadog, Loki, or OpenTelemetry to build proactive operational visibility.
• Programming Polyglot: Ability to debug across multiple languages, including Python, Node.js, and Go.

Trading & Specialized Knowledge

• Real-Time Systems: Understanding of systems where latency and reliability have direct financial consequences.
• Blockchain Infrastructure: Familiarity with node infrastructure, exchange APIs, wallet operations, and on-chain monitoring.
• Security Focus: Experience managing secrets, access controls, and production hardening for sensitive financial environments.
• System Reliability: Experience defining SLOs and building mature on-call practices.

Preferred Qualifications (Plus)

• Experience with OpenClaw agent deployments and workspace templates.
• Familiarity with Model Context Protocol (MCP) server deployment and auth management.
• Direct experience with Hyperliquid or other decentralized exchange (DEX) protocols.
• Background in fintech, market data infrastructure, or high-frequency trading systems.

Benefits

• Opportunity to build infrastructure for a new category of software (Autonomous AI Agents).
• High-autonomy environment with a focus on engineering excellence and technical ownership.
• Competitive compensation package commensurate with senior-level experience.
• Remote-first or flexible working arrangements (as specified by the client).

Interview Process

The interview process is designed to evaluate both technical depth and the ability to handle high-pressure production scenarios.

1. Initial Technical Screening: A conversation focused on previous experience building and scaling infrastructure from scratch.
2. Deep-Dive Technical Assessment: An evaluation of Kubernetes, IaC, and observability skills, often involving a real-world architectural challenge.
3. Systems & Reliability Interview: A session focused on incident response, zero-downtime deployments, and the specific nuances of trading infrastructure.
4. Final Leadership/Culture Fit: Meeting with key stakeholders to discuss the long-term vision of the AI agent platform.