4 months ago

Senior Data Engineer - Agentic AI Engineering

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Senior Data Engineer responsible for architecting scalable, secure data infrastructure to power AI-driven agents and multi-agent workflows. You’ll build and operate real-time and batch data pipelines, manage vector databases for low-latency contextual AI, and collaborate across AI/ML, platform, and DevOps teams to productionize experimental AI prototypes into enterprise-grade solutions.

Location: Denver

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Sr. Manager level

Key Responsibilities

•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.

Key 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:5+ yearsAIData EngineeringLLMAgentic AI

Skills:CommunicationCollaborationProblem-solvingTeamworkAttention to detail

Languages:English

Tech Stack:PythonSQLKafkaKinesisSnowflakeAWSAzureGCPPineconeMilvusAirflowDbtMLflow

Company Brief

boomi

Provides a cloud-native integration platform (iPaaS) enabling enterprises to connect applications, data, APIs and workflows for hybrid and multi-cloud environments. Offers tools for integration, API management, master data management, and workflow automation.

Industry: SaaS

Company Size: Enterprise (1,001+ employees)

Growth: Established Company

Valuation: Unicorn (USD 1B+)

Funding: Private Equity Backed

Headquarters: Chesterbrook, United States

Founded: 2000

Website LinkedIn

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boomi

4 months ago

Senior Data Engineer - Agentic AI Engineering

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Location: Denver

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Sr. Manager level

Key Responsibilities

•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.

Key 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:5+ yearsAIData EngineeringLLMAgentic AI

Skills:CommunicationCollaborationProblem-solvingTeamworkAttention to detail

Languages:English

Tech Stack:PythonSQLKafkaKinesisSnowflakeAWSAzureGCPPineconeMilvusAirflowDbtMLflow

Company Brief

boomi

Industry: SaaS

Company Size: Enterprise (1,001+ employees)

Growth: Established Company

Valuation: Unicorn (USD 1B+)

Funding: Private Equity Backed

Headquarters: Chesterbrook, United States

Founded: 2000

Website LinkedIn