Data Platform Engineer
Quick Summary
Monaco is the first revenue engine for startups. We're building the AI native platform that replaces legacy CRM and disparate sales point solutions. We're looking for a Senior Platform Engineer to help build Monaco's data and ML platform - the pipelines, context systems, and infrastructure that…
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, and…
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.
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.
Responsibilities
~1 min read- →
Build scalable pipelines and event-driven systems for ingesting, transforming, and serving data.
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Support ML workflows: training data, evaluation, embeddings, feature pipelines.
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Solve distributed systems challenges around reliability, latency, consistency, and scale.
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Improve observability, tooling, and developer experience for data, ML, and agent systems.
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.
San Francisco. We're an in-person team - 5 days in the office. At this stage, proximity genuinely accelerates product quality and team cohesion.
Location & Eligibility
Listing Details
- Posted
- February 10, 2026
- First seen
- May 17, 2026
- Last seen
- September 26, 2026
Posting Health
- Days active
- 132
- Repost count
- 0
- Trust Level
- 15%
- Scored at
- September 26, 2026
Signal breakdown
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