Senior Data Engineer – Agentic AI Engineering

🕒 June 26

⛰️ Colorado, Florida – Remote

⛰️ Colorado – Remote 🐊 Florida – Remote

💵 $138.9k - $173.6k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

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Boomi

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2000

☁️ SaaS

🔌 API

🏢 Enterprise

SaaS • API • Enterprise

Boomi is a leading provider of intelligent integration and automation solutions, empowering organizations to streamline business processes and accelerate digital transformation. With a strong focus on integration platform as a service (iPaaS), Boomi enables the secure deployment and management of APIs, integration of applications and data, and automation of workflows using AI-powered solutions. Trusted by over 20,000 customers, Boomi's platform supports a wide array of industries including manufacturing, healthcare, financial services, and more. Their extensive library of pre-built connectors, user-friendly interface, and robust customer support foster seamless integration and connectivity across cloud and on-premise environments. Recognized for its innovation and excellence, Boomi transforms complex integration challenges into manageable solutions, contributing significantly to efficiency and productivity in business operations.

📋 Description

• 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

• 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

• An overview of our benefits can be found here.