GenAI Data Engineer — Build Scalable AI Tools & Pipelines

Valiant Technologies LLC; Charlotte (NC); On-site; USD 89,000 - 126,000; Full time

Job summary

Valiant Technologies LLC in Charlotte, NC seeks an Agentic AI Data Engineer to design and build GenAI tooling, data pipelines, and observability improvements. You will own data labeling infrastructure and support secure, scalable AI workflows across business units.

You will collaborate with product and engineering leads to translate complex problems into tangible features, focusing on performance, reliability, and data integrity in a fast-paced environment.

Qualifications

• 5+ years in software/ML infrastructure engineering.
• Experience building full-stack internal GenAI tools (Python, FastAPI, Streamlit).
• Design and maintain data and ML pipelines and observability stacks.

Responsibilities

• Build full-stack internal GenAI tools enabling non-engineering teams to run LLM analysis over sensitive data, including scalable PII-masking pipelines.
• Design and maintain MCP servers/tools with strict identity and auth checks to run workflows from AI chat clients.
• Own and evolve labeling platform infrastructure (FastAPI, Celery, Redis, Labelbox) and manage large-scale data migrations and on-call support.
• Migrate observability stacks to OpenTelemetry, build dashboards and infrastructure-as-code for monitoring.
• Build and maintain data/ML pipelines (Airflow, Spark, Hive, Trino) across multiple business units.
• Collaborate with product and engineering leads to turn ambiguities into shipped features with measurable efficiency gains.

Skills

Python

Machine Learning

API development

Data analysis

Tools

FastAPI

Streamlit

Airflow

Spark

Hive

Trino

Redis

Celery

Labelbox

Job description

Valiant Technologies LLC in Charlotte, NC seeks an Agentic AI Data Engineer to design and build GenAI tooling, data pipelines, and observability improvements. You will own data labeling infrastructure and support secure, scalable AI workflows across business units.

You will collaborate with product and engineering leads to translate complex problems into tangible features, focusing on performance, reliability, and data integrity in a fast-paced environment.