Location: New York, United States (Hybrid) 

Hybrid | Full-time

Compensation: $180K - $320K

Our client operates a leading decentralized perpetual exchange, managing tens of billions in cumulative trading volume and bringing global markets—including commodities, forex, indices, stocks, and cryptocurrency—onchain with full self-custody.

To support next-generation scalability, our client is seeking a Senior Infrastructure & Data Engineer. This pivotal position involves spearheading high-impact infrastructure initiatives, migrating core applications to an advanced, state-of-the-art infrastructure layer, and optimizing high-volume data pipelines. The ideal candidate will design an environment where development teams can seamlessly self-serve up to 90% of their infrastructure needs, allowing this role to focus on high-level architecture, latency reduction, and strategic data engineering.

Key Responsibilities

• Infrastructure Migration & Evolution: Lead the migration of core services from legacy environments to a robust, highly optimized new infrastructure.
• Infrastructure as Code (IaC): Utilize 100% IaC principles to build, maintain, deploy, and manage all applications and services, prioritizing lower latency and higher visibility.
• Data Pipeline Optimization: Maintain, improve, and optimize a high-scale data pipeline to handle massive transaction volumes effectively, moving it beyond a standard setup to meet unique business requirements.
• Developer Empowerment: Build out a self-serve platform that enables internal software engineers to deploy new applications, request infrastructure, configure monitoring, and set up alerts autonomously.
• Internal Tooling Maturity: Mature and scale the in-house testing and validation tool ("Stack Orchestrator") so that developers can test applications locally in multiple environments and run multiple agents in parallel.
• Performance & Security: Drive down latency for critical-path applications by collaborating with application teams and contributing to application code. Maintain a proactive security posture by anticipating system vulnerabilities and running contained, simulated attacks using automated test suites and AI tools.

Requirements

Technical Experience

• Core Infrastructure Foundations: Mastery of networking, security protocols, identity and access control, and systems architecture.
• Containerization & Orchestration: Strong experience building and maintaining production workloads with Kubernetes, including deep knowledge of ecosystem best practices.
• DevOps & CI/CD Tooling: Hands-on expertise with Terraform, ArgoCD, GitHub Actions, Docker, Prometheus, and Grafana. Must be a strong advocate for pure Infrastructure as Code (IaC).
• Data Engineering & Storage: Proven experience with modern data modeling tools (such as DBT or SQLMesh) and data orchestration platforms (such as Airflow, Dagster, or Prefect).
• Database Management: Competency working with Postgres and ClickHouse for high-throughput applications.

Professional Attributes

• Security-First Mindset: A continuous focus on minimizing attack vectors and hardening system endpoints.
• AI Tool Integration: High proficiency using AI productivity tools effectively—validating outputs, setting up guardrails, and avoiding passive code reliance.
• Solution-Oriented Leadership: A commitment to unlocking velocity for development teams, prioritizing high-value impact, and defining an autonomous path forward.
• Collaborative & Adaptable: A low-ego, team-first mentality with a strong willingness to learn from cross-functional peers, including quants, software developers, and operations teams.
• Execution Alignment: Ability to practice healthy debate during the planning phase, followed by total commitment and execution once organizational decisions are finalized.

Benefits

• Competitive base salary.
• Comprehensive token and equity compensation package.
• Opportunity to work at the forefront of global decentralized financial infrastructure.



Interview Process

The interview process is structured across four distinct stages:

1. Hiring Manager Interview: An introductory conversation with the Backend Team Lead.
2. Technical Interview (System Design): A deep dive into architecture and infrastructure systems design.
3. Technical Interview (AI Coding Round): A practical hands-on session evaluating technical problem-solving and AI tool utilization.
4. Final Interview: A concluding discussion focused on cultural alignment and executive evaluation with the Chief Technology Officer (CTO)