Job description

Drata is building the trust layer between great companies - automating compliance, managing risk, and helping organizations prove trust continuously as they scale. We're Dratanauts: a global crew of 600+ professionals united by a culture that rewards integrity, ownership, and raising the bar, no matter where in the world we're working from. Why Join the Drata Team? At Drata, you're not maintaining legacy compliance software - you're building the agentic AI platform defining what trust looks like for the next generation of companies. Here's what makes the work itself worth showing up for: - Problems without a playbook: You'll work at the edge of AI and security, building agentic governance, continuous compliance, and real-time trust verification to solve problems that don't have an established answer yet. You're writing it as you go. - Real ownership, not just process: Our values center on owning outcomes and raising the bar, not checking boxes. You're expected to have opinions and back them. - A seat at the table: Your perspective is unique and valued. Open debate and diverse viewpoints are built into how decisions actually get made here, at every level. - Growth at rocketship speed: Drata is scaling fast, which means scope grows fast too. High performers get more ownership, visibility, and experience. - A crew, not just coworkers: Dratanauts consistently describe a "come as you are" culture with sharp, curious people—the kind of team that makes hard problems genuinely fun to solve. See what they say here drata.com and follow us on LinkedIn linkedin.com for company news, employee stories, and career updates. 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 is a research-focused role emphasizing experimentation and rigor over production engineering. You'll own the science behind how Drata's AI products retrieve, reason, and respond — and you'll work closely with AI and Software Engineers to turn validated approaches into production-ready systems. Drata's compliance platform is document-heavy: VRM Agent, AIQA, Trust Agent, policy-to-control mappers, and more all depend on high-quality information retrieval and reasoning. What you'll do: - 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 (controls ↔ risks ↔ requirements ↔ evidence) - 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 What you'll bring: - 6+ years of experience in applied research, data science, or ML with a focus on NLP, information retrieval, or knowledge systems - 2+ years of hands-on experience building or contributing to production AI/ML systems - Strong foundation in information retrieval: dense and sparse retrieval, embedding models, search relevance - Experience with RAG systems: chunking strategies, vector databases, retrieval optimization - Proficiency in evaluation methodology: metrics design, golden dataset creation, A/B testing, 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 - Bonus: Experience with compliance, legal, or document-heavy domains - Bonus: Publications or contributions in IR, NLP, or RAG evaluation How we support you: At Drata, our people are our strongest advantage—and we prove it with support that exceeds industry standards. Our total rewards package is designed to power your well-being, accelerate your growth, and keep your work-life balance thriving. Explore how we invest in your Life at Drata drata.com. - Shared Success: We provide stock equity to ensure that as the company grows, you share directly in that success. Equity gives every employee a sense of ownership and the opportunity to celebrate our wins together—because your contributions don’t just support our progress; they help drive our collective success. - Health & Wellness: Up to 100% employer-paid premiums for medical, dental, and vision coverage for employees and their dependents, along with comprehensive wellness benefits and healthcare concierge services designed to support your needs beyond traditional insurance. - Financial Well-being: A comprehensive suite of financial benefits, including a 401(k) plan, company-paid life and disability insurance, tax-advantaged spending accounts, and a range of discounted voluntary offerings to help you customize and strengthen your overall financial position. - Family Support: We want to support you in life's most important moments, so we offer a paid Parental Leave policy, after six months of employment. Employees also receive access to Kindbody fertility and family-building benefits and dedicated leave specialists who help guide you through the entire process. - Growth & Development: Generous annual stipends for both professional and personal development, empowering you to invest in your continued growth. You’ll also have access to a wide range of internal learning opportunities, ensuring you can build new skills, deepen your expertise, and advance your career with confidence. - Time Off & Flexibility: We believe that to do your best work, you should get the time you need for rest, rejuvenation and recovery. Drata offers a flexible vacation policy, paid holidays, and other perks to recharge. The expected base salary range for this role is between $157,000 - $252,000 and is listed to provide transparency. Actual base pay will vary based on multiple factors — market location, job-related knowledge, skills, experience, and overall alignment to the role. Candidates shouldn't expect automatic placement at any particular point within the range. Offer amounts are determined by the qualifications each candidate brings to the position. Total compensation may also include equity designed to provide meaningful ownership in the company, as well as health and wellbeing benefits.

Requirements

Must-haves

Why Join the Drata Team?
Real ownership, not just process: Our values center on owning outcomes and raising the bar, not checking boxes. You're expected to have opinions and back them.
A seat at the table: Your perspective is unique and valued. Open debate and diverse viewpoints are built into how decisions actually get made here, at every level.
Growth at rocketship speed: Drata is scaling fast, which means scope grows fast too. High performers get more ownership, visibility, and experience.
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.
Drata's compliance platform is document-heavy: VRM Agent, AIQA, Trust Agent, policy-to-control mappers, and more all depend on high-quality information retrieval and reasoning.
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 (controls ↔ risks ↔ requirements ↔ evidence)
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
6+ years of experience in applied research, data science, or ML with a focus on NLP, information retrieval, or knowledge systems
2+ years of hands-on experience building or contributing to production AI/ML systems
Strong foundation in information retrieval: dense and sparse retrieval, embedding models, search relevance
Experience with RAG systems: chunking strategies, vector databases, retrieval optimization
Proficiency in evaluation methodology: metrics design, golden dataset creation, A/B testing, 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

Nice-to-haves

Bonus: Experience with compliance, legal, or document-heavy domains
Bonus: Publications or contributions in IR, NLP, or RAG evaluation

Application prep

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Benefits

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Dental

Vision

401(K)

Parental Leave

Wellness