Principal Engineer, GenAI Architecture

Jobtailor; North Carolina; On-site; USD 120,000 - 160,000; Full time

Job summary

Jobtailor is seeking a Senior Data Engineer in North Carolina to design and build scalable data pipelines bridging on-premise systems and public clouds. You will develop Gen AI and agentic solutions for data curation, enrichment, analysis, and data quality checks, while owning data quality capabilities and governance across ingestion to retrieval.

Responsibilities include mentoring engineers, collaborating across teams, and shaping enterprise data platform architecture in regulated environments.

Qualifications

• 7+ years of Engineering experience or equivalent demonstrated through work
• 2+ years of experience building Gen AI and agentic solutions
• 3+ years of experience building scalable, production-grade data pipelines and data quality analysis
• 5+ years of experience with Python, with experience in ML frameworks
• Experience building or operating enterprise-grade AI-ready data platforms in regulated industries
• Hands-on experience building data pipelines between on-premise systems and public cloud environments
• Familiarity with embedding models and retrieval-augmented architectures
• Experience applying AI agents to data quality, data profiling, or analytics workflows
• Willingness to work on-site at the stated location
• Bachelor’s degree related to CS/ML/Stats desired

Responsibilities

• Design and build scalable, production-grade data pipelines moving data between on-premise systems and public clouds
• Build Gen AI and agentic solutions to automate data curation, enrichment, analysis, data quality checks, anomaly detection, and insights
• Own data quality and analytics capabilities, including validation frameworks, monitoring, profiling, and analytics tooling
• Build production-grade data and ML pipelines in Python using modern ML and Gen AI frameworks
• Own technical design across the ingestion-to-retrieval lifecycle: ingestion, transformation, storage, and governed data serving
• Establish engineering rigor through evaluation harnesses, data quality checks, drift monitoring, and reproducibility
• Collaborate with data engineers, platform engineers, and applied AI engineers on enterprise data platform architecture
• Partner with modeling and applied AI teams to improve production agent performance
• Mentor engineers in Gen AI, agentic solution design, scalable data pipeline engineering, and data quality practices
• Contribute to architectural decisions and technical reviews in cross-team and leadership forums

Skills

Gen AI Solutions Development

Data Pipeline Engineering

Python Programming

Data Quality Analysis

Collaboration

Mentoring

Technical Design

Education

Bachelor's Degree in Computer Science

Bachelor's Degree in Machine Learning

Bachelor's Degree in Statistics

Tools

Vector Databases

Analytics Tooling

Public Cloud Environments

Job description

• Design and build scalable, production-grade data pipelines moving and transforming data between on-premise systems and public cloud environments


• Build Gen AI and agentic solutions to automate data curation, enrichment, analysis, data quality checks, anomaly detection, and insight generation


• Own data quality and analytics capabilities, including validation frameworks, monitoring, profiling, and analytics tooling


• Build production-grade data and ML pipelines in Python using modern ML and Gen AI frameworks


• Own technical design across the ingestion-to-retrieval lifecycle, including ingestion, transformation, storage, and governed data serving


• Establish engineering rigor through evaluation harnesses, data quality checks, drift monitoring, and reproducibility


• Collaborate with data engineers, platform engineers, and applied AI engineers on enterprise data platform architecture


• Partner with modeling and applied AI teams to improve production agent performance


• Mentor engineers in Gen AI, agentic solution design, scalable data pipeline engineering, and data quality practices


• Contribute to architectural decisions and technical reviews in cross-team and leadership forums

Requirements

• 7+ years of Engineering experience, or equivalent demonstrated through work experience, training, military experience, or education


• 2+ years of experience building Gen AI and agentic solutions


• 3+ years of experience building scalable, production-grade data pipelines and data quality analysis


• 5+ years of experience with Python, with experience in ML frameworks


• Experience building or operating enterprise-grade, AI-ready data platforms in regulated industries


• Hands-on experience building data pipelines between on-premise systems and public cloud environments


• Familiarity with vector databases, embedding models, and retrieval-augmented architectures


• Experience applying AI agents to data quality, data profiling, or analytics workflows


• Willingness to work on-site at the stated location


• Bachelor's degree in Computer Science, Machine Learning, Statistics, or a related quantitative discipline is desired

Core Competencies

Demonstrates expertise in building scalable, production-grade data pipelines and Gen AI solutions, with a strong focus on data quality and analytics capabilities. Proficient in Python and modern ML frameworks, with experience in enterprise-grade data platforms and regulated industries.

Highest-signal resume keywords

• Data Pipeline Engineering


• Gen AI Solutions Development


• Python Programming


• Data Quality Analysis


• Enterprise Data Platforms

Hard Skills

• Data Pipeline


• Gen AI


• Machine Learning


• Python


• Data Quality Checks


• Anomaly Detection


• Data Transformation


• Data Profiling


• Monitoring Frameworks


• Embedding Models

Soft Skills

• Collaboration


• Mentoring


• Technical Design

Certifications & Qualifications

• Bachelor's Degree in Computer Science


• Bachelor's Degree in Machine Learning


• Bachelor's Degree in Statistics

Industry Keywords

• Regulated Industries


• Data Quality


• Data Curation


• Data Enrichment


• Data Analysis

Tools & Technologies

• Public Cloud Environments


• Vector Databases


• Analytics Tooling


• Governed Data Serving