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Alpaca is a US-headquartered global leader in agent-first brokerage infrastructure, serving hundreds of financial institutions across 40 countries with institutional-grade APIs. The company is backed by $400M in funding from top-tier investors including Spark Capital, Tribe Capital, and Y Combinator, and operates a globally distributed team of 400+ members.
As a Senior Software Engineer on the Market Data team, you will help build and scale the systems and services that form Alpaca's foundation, empowering millions of users trading billions of dollars in assets. The market data team is responsible for improving the overall architecture of Alpaca's data products (stocks, options, crypto, foreign exchange) and overseeing their public API structure and documentation for both streaming and historical endpoints.
You will influence the overall architecture of Alpaca's market data systems, design highly scalable mission-critical systems, and obsess over latency where every nanosecond counts. Key responsibilities include implementing backend services, leading architecture decisions where scalability and resilience matter, maintaining software quality and test coverage, participating in code reviews, troubleshooting incidents, and potentially being on-call for timely engineering projects.
Required qualifications include at least 4 years of experience working on systems at scale, proficiency with compiled imperative languages (Go, C, C++, Rust), SQL/relational database skills, familiarity with TCP/IP and UDP networking, proficiency with Linux/BSD and shell scripting, experience with Kubernetes or similar orchestration systems (primarily GKE), and experience with major cloud platforms (primarily GCP). You should have a proven track record of architecting and leading medium-scale projects involving multiple teams and a passion for financial markets.
Nice-to-have skills include market data experience, microservice architecture knowledge, low-latency application development, distributed key-value stores, CI/CD, observability and tracing, capacity planning, and familiarity with DevOps practices.
