Senior Cybersecurity Data Engineer - AI/ML SME

Socket.dev; Reston (VA); On-site; USD 159,600 - 239,400; Full time

Job summary

Workday is seeking a Senior Data Engineer – Cybersecurity in Reston, Virginia. This role involves managing AI/ML data infrastructure and integrating complex platform systems to support enterprise cybersecurity.

Ideal candidates will have over 5 years of data engineering experience, including proficiency with AWS SageMaker and strong skills in Python and SQL. The position promises a dynamic work environment requiring a blend of onsite and flexible work arrangements.

Qualifications

• 5+ years of data engineering experience, with at least 2+ years supporting machine learning platforms.
• Deep hands-on experience with cloud-native ML platforms.
• Expert knowledge in building REST APIs and utilizing streaming tools.

Responsibilities

• Design and maintain platform infrastructure for machine learning lifecycles.
• Manage enterprise Feature Store architecture.
• Optimize compute engines for heavy mathematical workloads.

Skills

Data engineering

Machine learning platforms

AWS SageMaker

Feature store frameworks

Apache Spark

Python

SQL

Tools

MLflow

GitHub Actions

GitLab CI

Job description

Your work days are brighter here.

We're obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we're shaping the future of work so teams can reach their potential and focus on what matters most.

About the Team

We are a newly formed, forward‑looking Cybersecurity Data Engineering & Enablement Team driving the future of our enterprise defense strategy. Our mission is to build a next-generation, centralized data lakehouse that unifies all security telemetry into a single, high-performance ecosystem.

About the Role

We are seeking a highly specialized Senior Data Engineer – Cybersecurity to serve as the Subject Matter Expert (SME) for AI/ML and Platform Integration. This critical role sits at the intersection of core data platform infrastructure, advanced analytics, and external system integrations.

Key Responsibilities

• AI/ML Data Infrastructure & Tooling: Design, provision, and maintain the platform infrastructure required for end-to-end machine learning lifecycles.
• Enterprise Feature Store Architecture: Design and manage the enterprise Feature Store. Ensure consistent, low-latency feature delivery.
• Vector Infrastructure for GenAI: Architect and maintain vector databases and indexing pipelines required to support Large Language Models (LLMs), RAG patterns, and semantic search.
• Platform Integration & API Management: Serve as the SME for how external applications interact with the data lakehouse.
• MLOps Collaboration & Automation: Partner closely with Data Scientists and MLOps teams to establish CI/CD automation for ML.
• Compute Optimization for Data Science: Configure and optimize compute engines tailored for heavy mathematical and data science workloads (e.g., Ray, Spark/EMR GPU instances).

About You

Basic Qualifications

• Experience: 5+ years of data engineering experience, with at least 2+ years dedicated to supporting machine learning platforms, MLOps, or complex platform integrations.
• ML Data Stack: Deep hands‑on experience with AWS SageMaker, MLflow, or equivalent cloud‑native ML platforms.
• Feature Stores & Vector DBs: Proven 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: Strong experience using Apache Spark / AWS EMR, Ray, or Dask.
• Integration Patterns: Expert knowledge of building REST APIs, Webhooks, and utilizing streaming tools (e.g., AWS Kinesis, Kafka).
• Languages & CI/CD: Advanced proficiency in Python (Pandas, NumPy, Scikit-Learn) and SQL. Extensive experience with GitHub Actions, GitLab CI, or Jenkins.

Other Qualifications

• Experience deploying and fine‑tuning open‑source LLMs or orchestrating AI agents using frameworks like LangChain or LlamaIndex.
• Experience with reverse‑ETL tools (e.g., Census, Hightouch) or enterprise integration platforms.

Compensation and Work Environment

• Primary Location: USA.VA.Reston
• Primary Location Base Pay Range: $159,600 USD – $239,400 USD
• Additional US Location(s) Base Pay Range: $144,400 USD – $258,000 USD
• We operate with a flexible work approach, requiring at least 50% of time in the office or in the field per quarter.

Workday is an Equal Opportunity Employer.