Senior Applied AI Engineer: RAG & GenAI Research

drata; San Francisco (CA); Hybrid; USD 167,000 - 226,000; Full time

Benefits offered by this job

Stock options

Health insurance

401(k) plan

Life & disability insurance

Fertility & family-building benefits

Professional development stipends

Flexible vacation policy

Job summary

Drata is seeking a Senior Applied AI Engineer to drive the quality and effectiveness of our AI systems through rigorous experimentation, evaluation, and applied research. This role emphasizes research over production engineering and involves turning validated approaches into production-ready systems.

You'll own the science behind information retrieval and reasoning for Drata’s compliance platform, collaborate with AI and Software Engineers, and stay current on RAG, agents, and LLM evaluation to

Qualifications

• 5+ years of experience in applied research, data science, or ML focusing on NLP/IR/knowledge systems.
• 2+ years building or contributing to production AI/ML systems.
• Strong foundation in information retrieval: dense and sparse retrieval, embeddings, search relevance.
• Experience with RAG systems: chunking, vector databases, retrieval optimization.
• Proficiency in evaluation methodologies: metrics design, golden datasets, A/B testing, statistical significance.
• Strong Python skills; notebook-driven research workflows.
• Experience communicating research findings to engineering teams and translating insights into actionable improvements.
• Bonus: experience with compliance, legal, or document-heavy domains.
• Bonus: publications in IR, NLP, or RAG evaluation.

Responsibilities

• Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML: chunking, embedding models, hybrid search, metadata filtering, semantic routing.
• Prototype GenAI workflows (including agentic systems) that map and reason over compliance objects.
• Explore ML + probabilistic approaches where GenAI is not the best fit: classifiers, ranking models, graph/link prediction, calibration, and structured prediction.
• Build and maintain evaluation frameworks: golden datasets, automated quality metrics, regression detection.
• Implement and tune ranking/reranking systems: cross-encoders, LLM-based rerankers, learning-to-rank, 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 RAG, agents, LLM evaluation, and relevance modeling; bring innovations into the product.

Skills

Applied AI Research

NLP

Information Retrieval

Python

Production ML

RAG

Evaluation

Job description

Drata is seeking a Senior Applied AI Engineer to drive the quality and effectiveness of our AI systems through rigorous experimentation, evaluation, and applied research. This role emphasizes research over production engineering and involves turning validated approaches into production-ready systems.

You'll own the science behind information retrieval and reasoning for Drata’s compliance platform, collaborate with AI and Software Engineers, and stay current on RAG, agents, and LLM evaluation to