Staff Infrastructure Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

$225K-$300K Verified - from the job posting source checked Jun 20, 2026

401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

125% above the BLS role benchmark for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type

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Weekend work

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Company

Company stage

Early Verified - from the job posting source checked Jun 20, 2026

Equity

Offered Verified - from the job posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Staff Infrastructure Engineer New York Office, Brooklyn, New York, United States About Espresso AI Espresso 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 Role As 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 On - Design, build, and scale Espresso's distributed execution and scheduling systems - Develop internal compute environments to safely offload workloads from Snowflake and Databricks - Implement compiler-style analysis and optimization of SQL workloads - Build infrastructure and data pipelines that support ML modeling and product features -

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