Staff Infrastructure Engineer

Espresso AIEspresso AI's mission is to use machine learning to automate performance engineering. Today, we help our customers reduce Snowflake and Databricks SQL compute costs by up to 70%, unlocking massive efficiency gains without requiring any workflow changes.More and more businesses are adopting data warehouses to manage invaluable data analytics workloads. Unfortunately, the costs of these workloads often grow exponentially over time, with no easy way for users to reduce cost — until now. Our next-generation, AI-based approach saves our users huge amounts of money.We're a well-funded, early-stage startup scaling quickly. Our most recent round was led by Nat Friedman and Daniel Gross.About the RoleAs a Staff Infrastructure Engineer, you will design and build the distributed systems that power Espresso's optimization engine. You will work across real-time scheduling, workload execution, performance analysis, and the internal compute environments that allow us to safely and efficiently offload warehouse workloads.You will own major architectural components, drive reliability and performance improvements, and collaborate closely with founders and engineering on long-term technical direction. This is a highly technical role with deep systems work at its core.What You'll Work OnDesign, build, and scale Espresso's distributed execution and scheduling systemsDevelop internal compute environments to safely offload workloads from Snowflake and DatabricksImplement compiler-style analysis and optimization of SQL workloadsBuild infrastructure and data pipelines that support ML modeling and product featuresImprove performance, reliability, and observability across the platformInfluence architectural decisions and contribute to engineering strategy as an early team memberMentor junior engineers as we scale the team, fostering strong engineering fundamentals and high-quality executionWhat You Bring7+ years software engineering experienceStrong fundamentals in systems design, performance engineering, and debuggingAbility to own complex technical projects end-to-endComfort operating across a broad range of infrastructure challenges and tackling whichever problems are most critical to the systemNice to HavesExperience at small startupsBackground in data warehouse cost optimizationExperience with workload orchestration, query execution, scheduling, or runtime systems is a bonusExposure to SQL optimizationExperience with software verificationWhat We OfferCompetitive salary and meaningful equity based on final leveling$225,000 - $300,000 Base Pay + EquityEmployee-friendly equity terms (early exercise)Health, dental, and vision insurance401k with 4% matchFree salads & gym membership