Founding Backend Engineer

NxT Level•New York, NY

9d•Onsite

About The Position

The role is described as a Senior Backend Engineer position owning the backend systems, data architecture, and core data model for an AI-native platform serving the chemical manufacturing industry. The engineer will work directly with the two co-founders and customers, translating customer problems into system requirements and owning work from design through shipping and production behavior. The platform’s data covers manufacturers, facilities, products, chemistries, accounts, and people; the role is responsible for keeping it correct, consistent, queryable, and useful as the product scales. This is a high-ownership role focused on building the company’s foundational data layer, including a knowledge graph and systems that support agent-powered research workflows. The engineer will make pragmatic architecture decisions, establish resilient operational practices, and contribute to product direction and technical priorities in a lean, in-person New York City team.

Requirements

6–10 years of professional software engineering experience.
Deep relational database expertise, preferably with PostgreSQL.
Strong TypeScript or Python experience.
Experience designing canonical data models that have evolved through real-world change.
Experience handling new data sources, new entity types, merges, splits, and changing business requirements.
Experience building or owning entity resolution, deduplication, matching, or reconciliation systems.
Strong understanding of deterministic rules, probabilistic matching, and human-in-the-loop review tradeoffs.
Experience building resilient backend systems with queues, retries, idempotency, and observability.
Pragmatic judgment around scale and the ability to explain tradeoffs clearly.
Comfort using AI tools as a core part of the engineering workflow.
Curiosity about how data should be structured for agents to work with it effectively.
Desire to work directly with customers and use customer conversations to inform technical decisions.
Excitement about working in person with the team in New York City five days per week.

Nice To Haves

Experience building knowledge graphs, data platforms, or graph-like relational models.
Experience with agentic workflows, AI research agents, or AI-native data products.
Experience working with messy real-world industrial, manufacturing, supply chain, or B2B data.
Experience building tools for sales intelligence, account research, market mapping, or portfolio analysis.
Experience at an early-stage startup with high ownership and direct founder collaboration.
Experience designing systems where AI agents are primary users or contributors to the data layer.

Responsibilities

Design and build backend systems that power an AI-native platform for chemical manufacturing.
Own the architecture and data model for manufacturers, facilities, products, chemistries, accounts, and people.
Build a knowledge graph that turns fragmented industry data into a coherent, queryable system.
Design systems that support agent-powered research workflows.
Structure data so AI agents can read, write, validate, and improve it over time.
Build and improve entity resolution, deduplication, reconciliation, and data quality workflows.
Make architecture decisions about what to build now, what to defer, and how to scale pragmatically.
Build resilient systems using queues, retries, idempotency, observability, and strong operational practices.
Work directly with customers to understand workflows, pain points, and product opportunities.
Partner with the co-founders to define product direction and technical priorities.
Ship quickly in a lean, high-agency environment without unnecessary process or handoffs.