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Drata

Automates security compliance and risk management.

Senior Applied AI Engineer

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USAHybrid

About the Job

Requirements

  • At least 6 years of experience in applied research, data science, or machine learning, focused on natural language processing, information retrieval, or knowledge systems.
  • At least 2 years of hands-on experience building or contributing to production artificial intelligence or machine-learning systems.
  • A strong foundation in information retrieval, including dense and sparse retrieval, embedding models, and search relevance.
  • Experience with retrieval-augmented generation systems, including chunking strategies, vector databases, and retrieval optimization.
  • Proficiency in evaluation methodology, including metrics design, golden dataset creation, A/B testing, and statistical significance.
  • Strong Python skills and comfort with notebook-driven research workflows.
  • Experience communicating research findings to engineering teams and translating insights into actionable improvements.

Responsibilities

  • Design and evaluate information access and reasoning strategies across retrieval-augmented generation, agents, and classic machine learning, including chunking, embedding models, hybrid search, metadata filtering, and semantic routing.
  • Prototype generative AI workflows, including agentic systems, that map and reason over compliance objects such as controls, risks, requirements, and evidence.
  • Explore machine-learning and probabilistic approaches where generative AI is not the best fit, including classifiers, ranking models, graph/link prediction, calibration, and structured prediction.
  • Build and maintain evaluation frameworks, including golden datasets, automated quality metrics, and regression detection.
  • Implement and tune ranking and reranking systems, including cross-encoders, large language model-based rerankers, learning-to-rank, and custom scoring functions.
  • Run experiments to validate hypotheses and quantify improvements before production rollout.
  • Debug failure modes and build error taxonomies across retrieval, reasoning, and generation.
  • Collaborate with AI and software engineers to hand off validated approaches for productionization.
  • Stay current on applied research in retrieval-augmented generation, agents, large language model evaluation, and relevance modeling, and bring innovations into the product.

Desired Qualifications

  • Experience with compliance, legal, or document-heavy domains.
  • Publications or contributions in information retrieval, natural language processing, or retrieval-augmented generation evaluation.

About the Company

Drata

Automates security compliance and risk management.

Drata provides a trust management platform that automates security compliance and risk management so teams can demonstrate their security posture to customers. It works by connecting to a company’s cloud, identity, HR, and developer tools to collect evidence and continuously monitor controls, enabling audits across many frameworks (e.g., SOC 2, ISO 27001, HIPAA, PCI DSS, GDPR) or custom ones. Compared with competitors, it combines continuous monitoring, broad framework coverage, deep integrations, and a dedicated trust center, plus AI-assisted content generation and governance features, offering an end-to-end compliance solution. The goal is to help organizations stay audit-ready, reduce the time and effort of compliance, and clearly show their security posture to customers and partners.

Company size
501-1,000
Company stage
Series C
Total funding
$328.2M
Headquarters
San Francisco, CA
Founded
2020

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