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Remote Apache Kafka Jobs
Browse remote Kafka positions — event streaming engineering, real-time data pipeline development, and ML feature computation roles at AI companies.
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At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are en...
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Runpod is the AI Developer Cloud. More than one million developers, from indie researchers to teams running frontier models in production, use Runpod...
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We are currently growing our support team at ClickHouse who provides excellent service to our customers around the world. We are seeking a Senior Tech...
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Pinecone is the leading vector database for building accurate and performant AI applications at scale in production. Pinecone's mission is to make AI...
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At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep do...
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Posted 2 weeks ago
Manager, Forward Deployed Engineering
Parloa
Berlin Office; London Office; Munich Office; Remotely in Germany; Remotely in the UK
Parloa’s mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates,...
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We are seeking a Platform Engineer to take ownership of deploying, managing, and evolving our multi-prem platform architecture across diverse customer...
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AlphaSense is the AI platform redefining market intelligence and workflow orchestration, trusted by thousands of leading organizations to drive faster...
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Role guide
What to expect in remote Kafka jobs
Apache Kafka is the backbone of real-time data infrastructure at AI companies. Remote Kafka jobs involve building event streaming pipelines, designing topic architectures, and integrating Kafka with ML feature stores and streaming ML inference systems. Engineers who combine Kafka expertise with Python and ML pipeline knowledge are particularly in demand.
What you'll work on
- Build real-time ML feature computation pipelines using Kafka Streams or ksqlDB
- Design event-driven architectures that trigger ML inference at scale
- Develop Kafka connectors to move data between databases and ML platforms
- Implement exactly-once processing for financial or safety-critical AI systems
What companies look for
- Kafka topic design — partitioning, retention, replication factor
- Consumer group management and offset handling for reliable processing
- Kafka Streams or ksqlDB for stream processing application development
Frequently asked questions
What remote Kafka jobs are available at AI companies?
Real-time data engineering and ML infrastructure roles where Kafka manages event streams. Most require Python alongside Kafka expertise and cloud platform (AWS MSK, Confluent Cloud) experience.
Do Kafka engineers need Spark knowledge for AI roles?
Often yes — particularly for roles combining batch and streaming processing. The Spark + Kafka combination is common in AI companies that need both real-time features and historical batch training data.
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