Data & AI Engineer

SolomonEdwards; Charlotte (NC); On-site; USD 120,000 - 180,000; Full time

Job summary

SolomonEdwards is seeking an AI Data Engineer to build and maintain the data infrastructure that powers enterprise AI applications and machine learning models. You will bridge software development, data science, and AI to ensure secure, scalable, and high-quality data.

Responsibilities include designing scalable ETL/ELT pipelines, enabling LLM/RAG workflows, implementing vector indexes and knowledge graphs, and enforcing data quality, governance, and MLOps practices in a dynamic client-focused

Qualifications

• Strong Python and SQL programming skills with experience in data pipelines.
• Experience building scalable ETL/ELT pipelines for structured and unstructured data.
• Familiarity with distributed processing and workflow orchestration tools.
• Experience with vector stores and search technologies for AI workloads.
• Knowledge of data governance, lineage, and regulatory compliance.

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines for enterprise data.
• Develop foundations for LLMs, RAG workflows, and semantic layers.
• Implement and optimize vector indexes, knowledge graphs, and retrieval systems.
• Establish data quality checks, bias detection, and lineage tracking.
• Deploy models to production with MLOps practices and monitoring.

Skills

Python

SQL

Java/TypeScript

Tools

Apache Spark

Airflow

Dagster

dbt

Pinecone

Elasticsearch/OpenSearch

Milvus

FAISS

Neo4j

AWS Neptune

Job description

SolomonEdwards is a national professional services firm offering financial, operational and technology consulting and operations support. Whether you need specialized consulting services or additional support to execute key initiatives, we bring the right people and expertise together to turn business challenges into value-creation opportunities.

About the Role

Our AI Data Engineer builds and maintains the data infrastructure, pipelines, and semantic layers that feed enterprise AI applications and machine learning models. They bridge the gap between software development, data science, and AI by ensuring machine learning models have secure, scalable, and high-quality data.

Responsibilities

• Pipeline Development: Design, build, and maintain scalable ETL/ELT pipelines for extracting, cleaning, and processing structured and unstructured enterprise data.
• AI/ML Integration: Build foundations for Large Language Models (LLMs) and Generative AI applications, including retrieval-augmented generation (RAG) and semantic layers.
• Vector & Graph Databases: Implement and optimize vector indexes, knowledge graphs, and hybrid retrieval systems to enhance AI reasoning and response quality.
• Data Quality & Governance: Establish validation checks, bias detection, and data lineage tracking to ensure model accuracy and regulatory compliance (e.g., SOC 2, HIPAA).
• MLOps & LLMOps: Deploy models into production, automate infrastructure, and monitor model performance, telemetry, and drift over time.

Qualifications

• Programming: Advanced proficiency in Python and SQL; familiarity with general-purpose languages like Java or TypeScript.
• Data Tools: Experience with distributed data processing and workflow orchestration (e.g., Apache Spark, Airflow, Dagster, dbt).
• Cloud AI Stacks: Hands-on experience with cloud AI and data platforms (e.g., AWS Bedrock, Google Vertex AI, Azure OpenAI).
• Search & Vector Stores: Proficiency in vector and search technologies like Pinecone, Elasticsearch/OpenSearch, Milvus, or FAISS.
• Knowledge Graphs (Preferred): Experience with graph databases (e.g., Neo4j, AWS Neptune) and query languages.

Preferred Skills

• Data Modeling Skills
• Database Design
• Distributed Computing
• Parallel Processing
• Algorithm Design
• Statistical AnalysisMathematical Modeling
• Probability Theory
• Statistics
• Programming Skills
• Software Engineering
• System Design
• Scalability Engineering
• Performance Optimization
• Code Optimization
• Testing
• Version Control
• Git for Data/ML

Pay range and compensation package

Data & AI Engineering offers competitive compensation packages.

Equal Opportunity Statement

We are committed to diversity and inclusivity in our hiring practices.