Staff Engineer, Data Platform (AI)

TL;DR

Staff Engineer, Data Platform (AI): Designing and evolving core data infrastructure for automated scientific discovery with an accent on ingestion frameworks, storage architecture, and orchestration patterns. Focus on building reliable pipelines for scientific data, implementing open lakehouse patterns, and translating research requirements into durable platform capabilities.

Location: Cambridge, MA USA or San Francisco, CA USA

Salary: $192,000 - $272,000 USD

Company

hirify.global is building an operating system for science that executes the entire scientific method autonomously to accelerate discovery across medicine, materials, and energy.

What you will do

• Design and evolve core data infrastructure for scientific and ML workflows, making principled build-vs-buy decisions.
• Build reliable pipelines to ingest data from laboratory instruments, public scientific datasets, and research literature.
• Operate and extend workflow orchestration systems to ensure observability, fault tolerance, and reproducibility.
• Define data models, schema evolution practices, and data contracts for long-term durability of assets.
• Partner with ML researchers and lab scientists to translate domain requirements into platform capabilities.
• Establish engineering standards and mentor the data platform team to raise the technical bar.

Requirements

• 8+ years of experience as a software or data engineer with a focus on data infrastructure.
• Proficiency in Python and SQL with a track record of writing production-quality code.
• Experience with relational and NoSQL databases, schema design, and query optimization at scale.
• Practical experience with cloud infrastructure (AWS) and containerized deployment (Kubernetes).
• Hands-on experience with modern table formats and open lakehouse patterns (Iceberg, Delta Lake, Hudi).
• Must be based in or able to work from Cambridge, MA or San Francisco, CA

Nice to have

• Experience with workflow orchestration tools such as Flyte, Airflow, or Dagster.
• Experience building infrastructure for agentic/LLM-driven workflows, including vector databases and RAG.
• Background in scientific computing, life sciences, or research software.
• Proficiency with AI-assisted development tools like Cursor or Claude Code.

Culture & Benefits

• Competitive base compensation with bonus potential and generous early-stage equity.
• Comprehensive U.S. and International benefits packages.
• High-velocity startup environment tackling problems of historic importance.
• Culture guided by truth, trust, curiosity, grit, and velocity.