Liquid AI, Inc. logo

Member of Technical Staff - Product Engineer (Internal Data & Agent Platform)

Job Overview

Location

San Francisco

Job Type

Full-time

Category

Full-Stack Engineer

Date Posted

April 22, 2026

Full Job Description

đź“‹ Description

  • • As a Member of Technical Staff - Product Engineer on Liquid AI's Internal Data & Agent Platform, you will build the foundational data infrastructure and agent layer that enables the company to operate with the agility of a small team while scaling enterprise-wide, replacing coordination overhead with visibility and guesswork with informed judgment.
  • • Day to day, you will design and implement the unified company data graph by integrating systems like GitHub, Linear, Slack, email, Zoom, calendars, Rippling, Vanta, Ramp, and Runway; build agents that surface performance signals, resource allocation suggestions, bottleneck detection, and opportunity visibility to leadership; own the full stack including data pipelines, APIs, agent orchestration, evaluations, and leadership-facing interfaces; and progress from observability to recommendations to partial automation using the progressive autonomy principle.
  • • Liquid AI, spun out of MIT CSAIL, builds general-purpose AI systems optimized for efficiency across data centers and on-device hardware, serving enterprises in consumer electronics, automotive, life sciences, and financial services, and is scaling rapidly with a mission to replace organizational friction with intelligent infrastructure.
  • • In this founding role with no legacy systems or playbook, you will gain deep experience in organizational data modeling, LLM-powered agent systems, full-stack internal platform development, and strategic decision-making through direct collaboration with leadership, shaping how an AI-native company operates at scale.

Skills & Technologies

Python
TypeScript
GitHub
Senior
Onsite

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Liquid AI, Inc. logo
Liquid AI, Inc.
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About Liquid AI, Inc.

Liquid AI builds foundation models and enterprise infrastructure for deploying large-scale generative AI in regulated industries. Its platform provides model training, fine-tuning, and inference services optimized for on-premises and air-gapped environments, emphasizing data privacy, security, and regulatory compliance. Founded by MIT researchers, the company serves financial services, healthcare, and government clients requiring controlled AI systems with transparent governance and full auditability.

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