"Backend Engineer, Data & Agent Platform" Jobs in United States

Backend Engineer, Data & Agent Platform

TensorStax · San Francisco

Strong software engineering experience in Python, with a focus on performance, reliability, and distributed systems. Hands-on experience building agentic AI applications, especially in domains such as computer control or

Backend Software Engineer, Agentic Data Platform-NYC (Tapestry)

Tapestry, Inc. · New York City

About Tapestry Tapestry is a group within Google working to build the AI-powered electric grid. We are tackling one of the world’s most important infrastructure challenges: helping the energy system become more visible,

Backend Software Engineer, Agentic Data Platform-NYC

Tapestry · New York City

About Tapestry Tapestry is a group within Google working to build the AI-powered electric grid. We are tackling one of the world’s most important infrastructure challenges: helping the energy system become more visible,

Senior Backend Engineer II, Data & Agentic Context Platforms

Fetch ·

Design, build, and operate scalable backend services and APIs that ingest, transform, retrieve, and serve context to agents and product applications. Own batch and real-time data flows, including event ingestion, transfo

Senior Backend Engineer — Data Platform & AI Agents

Jus Mundi SAS · New York City

📌 About the Role Jus Mundi is building the AI layer for international law and arbitration — turning a vast, multilingual corpus of case law, treaties, and legal analysis into answers practitioners can trust. We are now

At Commure, we're building the AI Operating System for healthcare, the foundation that defines how care is delivered, documented, and financed. Our platform spans the full care journey: Ambient AI and Dictation eliminati

About Radical AI Radical AI is replacing an R&D process that currently takes 10+ years and $100 million to produce a single discovery. Our self-driving lab platform combines AI with autonomous robotics to run expe

About Edra Edra is solving one of the hardest problems in enterprise AI: AI models are generic but company processes are specific. We build AI agents that learn how processes actually run, and then run their operations.