| Location | San Francisco, CA |
Monaco is building an AI-native revenue platform that replaces the fragmented GTM stack - CRM, sequencing, call recording, enrichment, pipeline management with one unified system, consolidating 6-10 disconnected tools into a single platform built for the AI era.
We launched publicly in Feb 2026, are already 65 people, and have strong early product-market fit generating millions in ARR within months of launch. Youll have the chance to both scale our core systems and build new features from 0 to 1.
Weve raised $85M in our Series B from Founders Fund, Benchmark, and Human Capital, and our founders previously led Brex, Apollo, and Clari.
Come join us if you want to be part of a high autonomy, high pace team reinventing one of the biggest categories in enterprise software.
The Role
Were looking for a Data Platform Engineer to help build Monacos data and ML platform - the pipelines, context systems, and infrastructure that power our AI-driven product. Youll work on the foundation that makes models, agents, and workflows actually useful in production.
This is a high-ownership role at the intersection of data engineering, distributed systems, and applied AI.
What Youll Do
Build scalable pipelines and event-driven systems for ingesting, transforming, and serving data.
Support ML workflows: training data, evaluation, embeddings, feature pipelines.
Solve distributed systems challenges around reliability, latency, consistency, and scale.
Improve observability, tooling, and developer experience for data, ML, and agent systems.
What Youll Bring
5+ years building data platforms, ML infrastructure, or backend systems.
Deep experience in technologies like PostgreSQL, Redis, Celery, Temporal, ElasticSearch or Turbopuffer, Kafka, Spark, Databricks or Snowflake, etc.
Ability to lead major architecture decisions and execute on them fast, maintain and scale production systems through rapid workload growth.
Location