DevOps Engineer

Stormlight Capital•Chicago, IL

1d•$225,000 - $325,000•Remote

About The Position

Stormlight Capital LLC is a high-frequency trading firm and market maker specializing in event contracts. Leveraging advanced technology and quantitative expertise, we deliver deep liquidity, efficient pricing, and robust risk management for our proprietary trading strategies. Continuous innovation and disciplined execution keep us at the forefront of event-based markets. We're seeking an exceptional DevOps Engineer to join our elite technology team. This is a high-impact position where your work directly influences our trading performance and bottom line. You'll architect and maintain the critical infrastructure that powers our derivatives trading operations, ensuring our systems can process millions of market data points and execute trades at lightning speed.

Requirements

3+ years of DevOps/Platform Engineering experience in high-performance environments
Expert-level proficiency with AWS and Google Cloud Platform services
Strong experience with DataBricks for big data and ML workloads
Proficiency with GitHub for version control and CI/CD workflows
Experience with monitoring tools (Prometheus, Grafana, DataDog, etc.)
Understanding of network optimization, kernel tuning, and hardware acceleration
Strong scripting abilities in Python, Bash, and/or Go
Experience with automation frameworks and configuration management tools
Understanding of software development lifecycle and testing methodologies

Nice To Haves

Previous experience in financial services, particularly trading firms or hedge funds
Knowledge of derivatives markets, trading systems, or market data feeds
Experience with streaming data platforms (Kafka, Pulsar, Kinesis, Chronicle Queue, Aeron)
Familiarity with quantitative finance or machine learning model deployment
Relevant certifications (AWS Solutions Architect, Google Cloud Professional, CKA/CKAD)

Responsibilities

Design, deploy, and maintain highly available, low-latency trading infrastructure across AWS, co-located servers, and Google Cloud platforms
Optimize system performance to achieve sub-millisecond latency requirements for critical trading applications
Build and maintain CI/CD pipelines using GitHub Actions for rapid, reliable deployments
Develop and maintain machine learning operations pipelines supporting our quantitative research and trading models
Manage DataBricks environments for large-scale data processing and model training workflows
Implement automated model deployment, monitoring, and rollback procedures
Ensure seamless integration between ML models and production trading systems
Implement comprehensive monitoring, alerting, and observability solutions for trading systems
Conduct performance analysis and capacity planning to ensure systems can handle peak market volatility
Lead incident response and post-mortem analysis for any system issues
Implement robust security measures for financial trading infrastructure