Founding Data Engineer (AI)

TL;DR

Founding Data Engineer (AI): Building and optimizing end-to-end data pipelines and ML models to transform enterprise data into AI-ready assets with an accent on agentic workflows and data ontology. Focus on designing internal tooling to automate data engineering and creating scalable abstractions for diverse customer environments.

Location: On-site in New York City

Compensation: $150K – $400K + Equity

Company

hirify.global is an applied AI company dedicated to transforming critical industrial institutions in sectors such as healthcare, manufacturing, and energy.

What you will do

• Build end-to-end pipelines and models to convert fragmented, messy enterprise data into high-leverage, AI-ready assets.
• Structure and normalize noisy datasets by defining data packs and ontologies for AI engineers.
• Develop internal products and tooling to make data work repeatable and compounding across different customer engagements.
• Collaborate with operators and product/AI engineers to translate high-value use cases into production data workflows.
• Determine technical strategy and make final calls on data models, storage, orchestration, and infrastructure tradeoffs.

Requirements

• Strong professional experience across Data Science, Data Engineering, and Machine Learning.
• Product-oriented mindset with a desire to build tools that increase operational leverage.
• Deep intuition regarding data requirements for modern LLM systems, including embeddings, retrieval, and context.
• High ownership and strong communication skills for direct collaboration with customer teams.
• Must be based in New York City for on-site work.

Nice to have

• Experience developing agentic or automated data-engineering tooling.
• Hands-on experience with modern cloud data platforms such as Databricks.
• Expertise with complex regulated data, specifically healthcare datasets (EHR, claims).
• Prior experience as a founding member or in a fast-paced startup environment.

Culture & Benefits

• Mission-driven environment focused on solving the most ambitious industrial problems.
• High-agency culture where employees are empowered to make decisions and shape ambiguity.
• "Intensity with Kindness" philosophy, balancing excellence and candor with vulnerability and trust.
• Outcome-focused approach where delivery is the primary strategy.
• Competitive base salary and equity stakes in a quickly growing AI team.