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Sr. AI Data Engineer

SYSTEM SOFT TECHNOLOGIES LLCNC🇺🇸United States

Why this role stands out

Advance your career as a Sr. AI Data Engineer with this hybrid role, offering a fantastic opportunity to build cutting-edge AI and Generative AI solutions within a reputable company. You'll thrive here if you possess strong Python, SQL, and cloud platform skills, coupled with a passion for data engineering and emerging AI technologies. This position is ideal for ambitious professionals eager to expand their expertise in a dynamic and collaborative environment.

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationNC, United States
DockerSQLGitApache SparkAWSETLEncryptionMLOpsSnowflakeAirflowApacheBigQueryDatabricksGoogle CloudKafkaPythonRedshiftGenerative AIAzureMachine LearningCI/CDAzure Data FactoryLangChainRAG

Job description

HYBRID - Charlotte NC

Only W2 - No Corp to Corp

OPEN TO SPONSOSRSHIP

PLEASE NO -OPT'S OR EAD'S

MUST HAVE

  • Programming: Strong Python and SQL skills.
  • Data Engineering: ETL/ELT, data modeling, data integration, batch processing, and streaming pipelines.
  • Big Data Technologies: Apache Spark, PySpark, Kafka, or similar technologies.
  • Cloud Platforms: AWS, Azure, or Google Cloud Platform.
  • Data Platforms: Snowflake, Databricks, BigQuery, Redshift, or Azure Data Lake.
  • AI/ML Data Engineering: Experience preparing datasets for machine learning and AI applications.
  • Generative AI: Understanding of LLMs, RAG architecture, embeddings, document processing, and vector search.
  • Vector Databases: Experience with Pinecone, Weaviate, Chroma, FAISS, or Azure AI Search is desirable.
  • Data Formats: JSON, Parquet, Avro, CSV, XML, and other structured or semi-structured formats.
  • DevOps: Git, CI/CD pipelines, Docker, orchestration, and automated testing.
  • Workflow Orchestration: Airflow, Azure Data Factory, AWS Glue, or similar tools.

Preferred Qualifications

  • Experience building data pipelines for Generative AI and enterprise AI solutions.
  • Familiarity with frameworks such as LangChain or LlamaIndex.
  • Experience with feature engineering, feature stores, and ML data preparation.
  • Knowledge of model serving, MLOps, and data observability.
  • Experience processing unstructured data, including documents, images, and text.
  • Understanding of data governance, PII handling, encryption, and enterprise security.
  • Relevant bachelor's or master's degree in Computer Science, Data Engineering, or a related field.

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