Backend and Platform Engineer (Python)

Location: Hybrid in Seattle, WA, with preference for candidates within commuting distance of offices in San Francisco, Seattle, or New York City

Salary: $165,000–$205,000 base salary per year, excluding equity and benefits

Company

hirify.global is an AI-driven causal marketing platform that helps leading brands measure the impact of marketing spend and optimize growth.

What you will do

• Build and evolve Python data pipelines that fetch, aggregate, and transform KPI data from BigQuery across multiple geographies and granularities.
• Extend the statistical estimation library with new estimators, improved standard error methods, and performance optimizations for large panel datasets.
• Improve the Metaflow-based orchestration system that schedules and runs thousands of daily experiment analyses on Kubernetes.
• Design monitoring, alerting, and self-healing patterns for autonomous production pipelines.
• Collaborate with applied scientists to turn research prototypes into tested, observable production code.
• Work with product engineers to publish analysis results through customer-facing APIs and frontend applications, while participating in on-call rotation.

Requirements

• 3+ years of experience building and shipping production software systems.
• Strong Python proficiency with pandas, numpy, pytest, and poetry.
• Experience with large datasets, data pipelines, ETL systems, SQL, and analytical databases such as BigQuery or Snowflake.
• Experience deploying, monitoring, and operating services in cloud-native production environments; GCP knowledge is preferred.
• Ability to read statistical code, understand experimental design concepts, and collaborate effectively with scientists and researchers.
• Excellent communication skills and experience using AI development tools such as Claude, Cursor, or Copilot in daily software development.

Nice to have

• Earlier-stage startup experience.
• Familiarity with statistical or scientific computing, including scipy, scikit-learn, or Bayesian methods.
• Experience with Kubernetes, containerized workloads, event-driven architectures, experimentation platforms, A/B testing infrastructure, or causal inference systems.
• Experience working across multiple interconnected repositories with coordinated release cycles.

Culture & Benefits

• High-performance, low-ego environment with ownership, inclusion, collaboration, and growth.
• Flexible paid time off.
• Equity participation and health, dental, and vision insurance.
• Work-from-home stipend and new-parent leave.
• Office lunches in San Francisco, New York City, and Seattle, plus events and offsites.