Senior Cybersecurity Data Engineer - AI/ML SME
$144,400–$258,000 year
Hybrid · Reston, Virginia, United States
Job Summary
Senior Cybersecurity Data Engineer – AI/ML SME: SME for AI/ML and platform integration within a cloud-native data lakehouse for security telemetry. Responsibilities include designing and provisioning infrastructure for end-to-end ML lifecycles, managing enterprise feature store architecture, building vector DB and GenAI pipelines, API management and data connectors, enabling CI/CD automation for ML, and optimizing compute for large-scale data science. Required skills include AWS SageMaker, MLflow, Feast or SageMaker Feature Store, vector databases (Pinecone, Milvus, Qdrant, Pgvector), Spark/AWS EMR, Ray/Dask, REST APIs and streaming (Kinesis/Kafka), Python and SQL, GitHub Actions/Jenkins, experience with open-source LLMs (LangChain/LlamaIndex) and reverse-ETL tools (Census, Hightouch). Salary ranges are stated per location with a flexible, hybrid/remote-friendly work model.
Required Qualifications
- 5+ years of data engineering experience
- at least 2+ years dedicated to supporting machine learning platforms, MLOps, or complex platform integrations
- Deep hands-on experience with AWS SageMaker, MLflow, or equivalent cloud-native ML platforms
- Experience implementing feature store frameworks (e.g., Feast, SageMaker Feature Store) and vector databases (e.g., Pinecone, Milvus, Qdrant, or Pgvector)
- Distributed compute & ML libraries (Spark, AWS EMR, Ray, Dask)
- Experience building REST APIs, Webhooks, and streaming tools (AWS Kinesis, Kafka) for real-time integration
- Proficiency in Python and SQL; experience with GitHub Actions, GitLab CI, or Jenkins
- Experience deploying and fine-tuning open-source LLMs or orchestrating AI agents (LangChain, LlamaIndex)
- Experience with reverse-ETL tools (Census, Hightouch) or enterprise integration platforms
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