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Full timeTechnology

Data Platform Engineer

MonacoSan Francisco🇺🇸United States

Why this role stands out

You'll have the opportunity to build the foundational data and ML platform for an AI-native revenue product, working on scalable pipelines and distributed systems at a rapidly growing, well-funded company. This high-ownership role is perfect for a mid-senior engineer with a passion for data engineering, distributed systems, and applied AI who thrives in a high-pace, high-autonomy environment. Apply now to make a significant impact on a product reinventing enterprise software.

Quick overview

SeniorityMid Senior
Employment typeFull Time
Work modeOn Site
LocationSan Francisco, United States
SnowflakeDatabricksKafkaPostgreSQLRedis

Job description

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. You'll have the chance to both scale our core systems and build new features from 0 to 1.

We've 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

We're looking for a Data Platform Engineer to help build Monaco's data and ML platform - the pipelines, context systems, and infrastructure that power our AI-driven product. You'll 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 You'll 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 You'll 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

  • San Francisco. We're an in-person team - 5 days in the office. At this stage, proximity genuinely accelerates product quality and team cohesion.

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ApplyOr apply on Monaco's site