About The Position

This role is hybrid, working onsite in Wayne, PA - 1 day per week, typically Tuesday or Thursday. ARE YOU READY TO HELP BUILD THE MISSING AI OPERATIONAL LAYER POWERING THE FUTURE OF ENTERPRISE CUSTOMER EXPERIENCE? Our client is a fully funded, AI SaaS startup currently operating in stealth mode and preparing for rapid enterprise scale. They are building a next generation operational intelligence platform focused on solving massive workflow, visibility, and execution challenges across complex enterprise networks. Their platform combines AI workflows, real time data systems, and enterprise grade infrastructure to modernize how large organizations manage customer experience at scale. Our client is currently in rapid growth mode, actively expanding its engineering organization as it continues advancing conversations and partnerships with enterprise customers across the industry. This is a rare opportunity to make a BIG Impact at an early stage high growth startup. They have strong funding, experienced founders, real enterprise traction with product market fit, and a highly technical product vision centered around AI native infrastructure from day one.

Requirements

  • 3-7+ years of experience building, shipping, and supporting production-grade data pipelines, infrastructure, and distributed systems used in real-world customer environments.
  • Experience with AI/LLM infrastructure, embeddings, vector databases, or RAG systems.
  • Strong understanding of multi-tenant architecture and enterprise-grade data systems.
  • Strong SQL fundamentals and deep PostgreSQL experience.
  • Strong Python experience for data engineering and infrastructure work.
  • Experience with dbt, Dagster, Airflow, Kafka, or equivalent modern tooling.
  • Experience working within SaaS or AI-native platforms.
  • Startup mindset with strong ownership, communication, and execution skills.
  • Extremely organized and self sufficient with the ability to work independently in a fast paced environment with changing requirements.
  • Excited to work in a startup environment with a track record of being adaptable to changing priorities in a fluid high growth environment.

Responsibilities

  • Build and scale production grade data pipelines and infrastructure.
  • Design warehouse architecture, schema strategy, and data models for a multi-tenant SaaS platform.
  • Support AI workflows, embeddings pipelines, vector databases, and retrieval systems.
  • Build real-time and batch integrations across enterprise systems and third-party platforms.
  • Own data quality, observability, lineage, and monitoring systems.
  • Partner closely with Applied AI Engineers on production AI infrastructure.
  • Support enterprise-grade security, compliance, and regulated data environments.
  • Help define long-term data architecture and platform scalability strategy.

Benefits

  • 10 days PTO
  • Equity
  • Paid holidays
  • Work from home equipment provided, including laptop and monitors
  • Health, medical, and vision coverage
  • Early stage startup environment with direct impact on product and company growth
  • Opportunity to help shape the future of an AI native enterprise platform
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