Analytics Engineer (AI)

Location: Hybrid in San Mateo, United States

Salary: $180,000–$240,000 annually, plus equity.

Company

hirify.global provides infrastructure for building, training, and serving specialized AI models across text, image, embedding, audio, and multimodal workloads.

What you will do

• Own a function's data domain end to end, including measurement definitions, modeling, roadmap, and delivery.
• Build and maintain pipelines in BigQuery and Coalesce using shared data standards, governance, and certified definitions.
• Create authoritative models and dashboards for Finance, Product-Led Growth, People, or Partnerships.
• Monitor variance, anomalies, mix shifts, and completeness gaps, communicating actionable findings to stakeholders.
• Contribute improvements to shared data platform frameworks, standards, tooling, and developer experience.
• Automate reconciliation, anomaly detection, reporting, and operational handoffs with agentic and LLM-powered workflows.

Requirements

• 5+ years of experience in data analysis, analytics engineering, and/or data engineering.
• Strong SQL and data visualization skills, including schema design, query development, and dashboard creation.
• Working knowledge of data engineering workflows, pull requests, and code review.
• Strong analytical thinking and the ability to investigate root causes and explain ambiguous findings.
• Clear communication with non-technical stakeholders and a bias toward building systems instead of managing recurring manual processes.
• Python proficiency and experience with LLM-powered agents, modern BI, transformation tooling, AI infrastructure, developer tools, or usage-based platforms are preferred.

Nice to have

• Experience with Sigma, Looker, Tableau, dbt, Coalesce, or similar tools.
• Experience with billing and revenue systems, product analytics and experimentation, HRIS/ATS platforms, workflow automation, or partner and marketplace economics.
• Background with token pricing, GPU-hour metering, model mix, or cost-per-request metrics.

Culture & Benefits

• Work on low-latency inference, scalable model serving, and other AI infrastructure challenges.
• Collaborate with engineers and AI researchers on emerging technologies.
• Own business data and automation infrastructure with direct impact and limited bureaucracy.
• Equity is included in the compensation package.
• Inclusive, equal-opportunity workplace committed to diversity.