AI Data Engineer

Valiant Technologies LLC; Dallas (TX); On-site; USD 120,000 - 170,000; Full time

Job summary

Valiant Technologies LLC is seeking a Data Engineer to design and maintain data infrastructure powering AI/ML initiatives, including data pipelines for model training, retrieval-augmented generation, and production ML systems across analytics and AI usage.

You will own ingestion and normalization of structured and unstructured data, develop vector embedding pipelines, feature stores, and RAG support, ensure data lineage and governance, optimize for cost and performance, and collaborate with ML

Qualifications

• Strong SQL and one of Python or Scala for pipeline development.
• Experience with a cloud data platform.
• Experience with orchestration tools such as Airflow and dbt.
• Understanding of embedding models, vector search, and RAG patterns.
• Experience with unstructured data processing.
• Familiarity with ML lifecycle concepts.

Responsibilities

• Design and build pipelines to ingest, clean, and transform data for AI/ML use cases.
• Build and maintain vector embedding pipelines and support vector database integration.
• Develop feature stores/pipelines for ML model training and inference.
• Implement data pipelines supporting RAG architectures and metadata tagging.
• Partner with ML engineers/data scientists to understand data requirements for model training and evaluation.
• Ensure data lineage, quality, and governance across pipelines feeding AI systems.
• Optimize pipelines for cost and performance.
• Support MLOps/LLMOps workflows including dataset versioning and reproducibility.

Skills

SQL

Python/Scala

Cloud data platform

Orchestration tools

Embedding models

Unstructured data processing

ML lifecycle concepts

Tools

Airflow

dbt

Snowflake Cortex

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Job Description:

We're looking for a Data Engineer to build and maintain the data infrastructure powering our AI/ML initiatives — including data pipelines for model training, retrieval-augmented generation (RAG), and production ML systems. This role sits at the intersection of data engineering and applied AI, ensuring high-quality, well-governed data is available for both traditional analytics and AI consumption.

Key Responsibilities:

• Design and build pipelines to ingest, clean, and transform structured and unstructured data (documents, PDFs, transcripts, logs) for AI/ML use cases
• Build and maintain vector embedding pipelines and support vector database integration
• Develop feature stores/pipelines for ML model training and inference
• Implement data pipelines supporting RAG architectures — chunking strategies, embedding refresh cycles, metadata tagging
• Partner with ML engineers/data scientists to understand data requirements for model training and evaluation
• Ensure data lineage, quality, and governance across pipelines feeding AI systems
• Optimize pipelines for cost and performance (e.g., Dynamic Tables, streaming ingestion)
• Support MLOps/LLMOps workflows — versioning datasets, tracking data used in model training for reproducibility and compliance
• Implement entitlement/access control logic so AI systems only access data they're authorized to use

Required Skills/Experience:

• Strong SQL + one of Python/Scala for pipeline development
• Experience with a cloud data platform
• Experience with orchestration tools (Airflow, dbt)
• Understanding of embedding models, vector search, and RAG patterns
• Experience with unstructured data processing
• Familiarity with ML lifecycle concepts

Nice to have:

• Experience with Snowflake Cortex, Cortex Search, or similar in-warehouse AI tooling
• Experience in a regulated industry (financial services) with data entitlement/compliance requirements
• Exposure to LLM application frameworks (LangChain, Llama Index)

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.