Senior Data Engineer – Agentic AI Engineering

This is a fully remote position, open to applicants in Colorado, +1 more state.

📋 Description

• Design and implement scalable, secure, and observable data infrastructure to support LLM-based agents, multi-agent systems, and tool-utilizing AI workflows.

• Create and manage robust batch and real-time data pipelines that facilitate embeddings, RAG systems, and agent memory frameworks.

• Develop and oversee vector database solutions to ensure low-latency retrieval and contextual intelligence for AI applications.

• Establish data frameworks for the training, evaluation, benchmarking, and ongoing enhancement of agentic AI systems.

• Enforce solid data governance, quality controls, lineage tracking, and PII/security compliance across AI data platforms.

• Work collaboratively with AI/ML, platform, and DevOps teams to turn experimental AI prototypes into enterprise-level solutions.

• Enhance data systems for performance, scalability, reliability, and cost-effectiveness within cloud environments (AWS, Azure, or GCP).

⛳️ Requirements

• Over 5 years of experience in developing and managing large-scale data platforms as a Data Engineer.

• Proficient programming skills in Python and SQL for creating scalable and efficient data solutions.

• Practical experience in designing batch and real-time data pipelines, including streaming systems such as Kafka or Kinesis.

• Familiarity with modern data platforms and cloud environments (AWS, Azure, or GCP), including tools like Snowflake.

• Strong comprehension of LLM/AI data workflows, encompassing embeddings, RAG pipelines, evaluation datasets, and vector databases (Pinecone, Milvus).

• Experience using DataOps/MLOps tools like Airflow, dbt, Lavender, and MLflow for orchestration and lifecycle management.

• In-depth knowledge of data quality, governance, and security, including handling PII, access controls, lineage, and ensuring data reliability.

🏝️ Benefits

• An overview of our benefits can be found here.