{"id":69396,"url":"https://alion.io/job/espresso-staff-infrastructure-engineer","title":"Staff Infrastructure Engineer","company":{"id":99093,"name":"Espresso AI","domain":"espresso.ai","url":"https://alion.io/company/espresso-2","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":225000,"max":450000,"currency":"USD","period":"year","gross":null,"usd_annual":450000},"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Databricks","optional":false},{"name":"Machine Learning","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2024-09-17T21:24:08Z","employer_posted_date":"2024-09-17","last_verified_at":"2026-10-29T06:46:39Z","board_verified":true,"closed_at":null,"days_open":771,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":771},"description":"About Espresso AI\nEspresso 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.\nMore 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.\nWe’re a well-funded, early-stage startup scaling quickly. Our most recent round was led by Nat Friedman and Daniel Gross.\nAbout the Role\nAs 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.\nYou 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.\nWhat You’ll Work On\nDesign, build, and scale Espresso’s distributed execution and scheduling systems\n\nDevelop internal compute environments to safely offload workloads from Snowflake and Databricks\n\nImplement compiler-style analysis and optimization of SQL workloads\n\nBuild infrastructure and data pipelines that support ML modeling and product features\n\nImprove performance, reliability, and observability across the platform\n\nInfluence architectural decisions and contribute to engineering strategy as an early team member\n\nMentor junior engineers as we scale the team, fostering strong engineering fundamentals and high-quality execution\n\nWhat You Bring\n7+ years software engineering experience\n\nStrong fundamentals in systems design, performance engineering, and debugging\n\nAbility to own complex technical projects end-to-end\n\nComfort operating across a broad range of infrastructure challenges and tackling whichever problems are most critical to the system \n\nNice to Haves\nExperience at small startups\n\nBackground in data warehouse cost optimization\n\nExperience with workload orchestration, query execution, scheduling, or runtime systems is a bonus\n\nExposure to SQL optimization\n\nExperience with software verification\n\nWhat We Offer\nCompetitive salary and meaningful equity based on final leveling\n$225,000 - 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