Senior Data Engineer – Agentic AI Engineering

Boomi

Senior Data Engineer at Boomi architecting data infrastructure for AI initiatives. Building scalable, secure, and observable data frameworks to support agentic AI systems.

Posted 6/26/2026full-timeRemote • Colorado, Florida • 🇺🇸 United StatesSenior💰 $138,862 - $173,578 per yearWebsite

Tech Stack

Tools & technologies

AirflowAWSAzureCloudGoogle Cloud PlatformKafkaPythonSQL

About the role

Key responsibilities & impact

Architect and build scalable, secure, and observable data infrastructure to power LLM-based agents, multi-agent systems, and tool-using AI workflows.
Design and operate robust batch and real-time data pipelines supporting embeddings, RAG systems, and agent memory frameworks.
Develop and manage vector database solutions to enable low-latency retrieval and contextual intelligence for AI applications.
Build data frameworks for training, evaluation, benchmarking, and continuous improvement of agentic AI systems.
Implement strong data governance, quality controls, lineage tracking, and PII/security compliance across AI data platforms.
Collaborate with AI/ML, platform, and DevOps teams to productionize experimental AI prototypes into enterprise-grade solutions.
Optimize data systems for performance, scalability, reliability, and cost efficiency across cloud environments (AWS, Azure, or GCP).

Requirements

What you’ll need

5+ years of experience building and operating large-scale data platforms as a Data Engineer.
Strong programming expertise in Python and SQL for developing scalable and efficient data solutions.
Hands-on experience designing batch and real-time data pipelines, including streaming systems like Kafka or Kinesis.
Experience with modern data platforms and cloud environments (AWS, Azure, or GCP), including tools like Snowflake.
Strong understanding of LLM/AI data workflows, including embeddings, RAG pipelines, evaluation datasets, and vector databases (Pinecone, Milvus).
Experience with DataOps/MLOps tools such as Airflow, dbt, Lavender, and MLflow for orchestration and lifecycle management.
Strong knowledge of data quality, governance, and security, including PII handling, access controls, lineage, and ensuring data reliability.

Benefits

Comp & perks

An overview of our benefits can be found here.

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Hard Skills & Tools

PythonSQLdata pipelinesbatch processingreal-time processingvector databasesdata governancedata qualitydata lineagedata security