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AbsenceSoft Logo AbsenceSoft · IT - Software Development

AI Data Engineer

United States 152000.00 - 190000.00 USD / Year · Job Posted January 11, 2026
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Job Description

We’re seeking a Data Engineer to design and manage the data pipelines, platforms, and tools that power intelligent AI applications. You will work closely with data scientists, AI software engineers, and product teams to ensure our ML and LLM workloads are backed by scalable, secure, and high-performance data infrastructure. This is a hands-on, high-impact role where reliability and flexibility of data architecture is paramount.

Job Responsibility

  • Design, build, and maintain data pipelines for structured, unstructured, and semi-structured data sources
  • Develop and optimize data models, ETL processes, and batch/streaming data infrastructure
  • Partner with data scientists to support training, evaluation, and deployment of ML and LLM models
  • Implement scalable architectures for embeddings, vector databases, and retrieval pipelines
  • Enable real-time and offline analytics workflows using best-in-class data engineering practices
  • Ensure data quality, lineage, observability, and governance across all data products
  • Deploy secure, cloud-native data infrastructure (AWS, Azure, GCP) for high-volume AI workloads
  • Contribute to the design of feature stores and MLOps platforms for continuous learning and model updates
  • Collaborate on Responsible AI workflows to ensure compliant data usage and access controls
  • Continuously evaluate new tools and technologies for improving performance, reliability, and agility

Requirements

  • 5+ years of experience as a Data Engineer building large-scale, production-grade data pipelines
  • Strong command of SQL, Python, and distributed data processing frameworks (Spark, Flink, Beam)
  • Hands-on experience with ETL/ELT tools and orchestration systems (Airflow, dbt, Prefect, Dagster)
  • Familiarity with cloud-native data platforms (Snowflake, BigQuery, Redshift, Databricks)
  • Experience supporting ML/AI workloads and collaborating with model development teams
  • Knowledge of vector databases (FAISS, Pinecone, Weaviate) and embeddings management
  • Understanding of data privacy, access control, and compliance in regulated environments
  • Proficiency in modern DevOps tooling for data infrastructure (Docker, Terraform, CI/CD)
  • Ability to work autonomously and thrive in a fast-paced, collaborative environment

Nice to have

  • Cloud: AWS (Redshift, S3, Lambda), Azure (Data Lake, Synapse), GCP (BigQuery, Cloud Functions)
  • Streaming: Kafka, Kinesis, Pub/Sub, Spark Streaming, Apache Flink
  • Workflow Tools: dbt, Airflow, Dagster, Prefect
  • Storage & Processing: Snowflake, Databricks, Parquet, Delta Lake
  • Vector Search: FAISS, Pinecone, Weaviate, txtai

What we offer

  • Impact that matters
  • Flexibility and trust
  • Growth and development
  • Competitive rewards
  • Time for life
  • Belonging and balance
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