Amazon Web Services (AWS), Apache Spark, Artificial Intelligence (AI), Automation, Cloud Computing, Data Management, Data Modeling, Data Quality, GCP (Good Clinical Practices), Memory Management, Microsoft Windows Azure, Multiplatform/Cross-Platform, Python Programming/Scripting Language, SQL (Structured Query Language), Scalable System Development, Use Cases
Role Name: Pulse GenAI Engineering build Sr Data Engineer
Location: Charlotte, NC -Onsite
JOB DESCRIPTION:
Job Description
We are looking for a skilled and innovative Senior Data Engineer to join our growing data and AI team In this role you will be responsible for building scalable data infrastructure ensuring data quality and driving the integration of cuttingedge AI and agentic systems into our data platform
Key Responsibilities
Data Engineering
Build robust data models schemas and transformations that support analytics and AI workloads
Ensure strong data quality reliability lineage and observability across the platform
Design and maintain scalable data pipelines for batch and realtime processing
Agentic AI Engineering
Design and support Agentic AI systems including autonomous agents capable of reasoning planning and acting
Implement tool usage memory management and feedbackselfrefinement loops
Architect and manage multiagent orchestration and task decomposition
Integrate LLMs into data pipelines for reasoning enrichment and automation
Partner with ML and AI teams to productionize agentdriven use cases
Support AI patterns such as RAG embeddings and prompt engineering
Required Qualifications
4 years of experience in Data Engineering or a related field
Proficiency in SQL Python and distributed data frameworks Spark Databricks etc
Handson experience with cloud data platforms AWS GCP or Azure
Familiarity with LLMs vector databases and AIML pipelines
Strong understanding of data modeling data quality and observability principles
Preferred Qualifications
Experience building agentic or multiagent AI systems
Knowledge of RAG pipelines embeddings and prompt engineering
Familiarity with tools like LangChain LlamaIndex or similar frameworkse
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