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Drata

Automates security compliance and risk management.

Senior Product Engineer 2 - Audit

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USAHybrid

About the Job

Requirements

  • Seven or more years of software engineering experience, including a demonstrated record of shipping full-stack features in production.
  • Two or more years of experience working on AI-powered product features.
  • Strong proficiency in React and TypeScript, including responsive, interactive user interfaces that handle asynchronous, streaming, and real-time data.
  • Solid Python, Node.js, and TypeScript skills, with experience designing and consuming APIs integrated with LLM providers, orchestration frameworks, or AI services.
  • Hands-on experience with LLM APIs such as OpenAI or Anthropic; practical understanding of prompt engineering, context management, retrieval-augmented generation, quality evaluations, and structured outputs.
  • Familiarity with agent frameworks such as LangGraph, LangChain, or custom runtimes, and building product interfaces for multi-step agent workflows.
  • Experience implementing streaming response patterns such as server-sent events, WebSockets, or chunked HTTP, and building interfaces for progressive, partial, and uncertain outputs.
  • Strong user-experience intuition and the ability to assess whether product interactions work for users as well as technically.
  • Track record of collaborating with AI/ML engineers, product managers, and designers in cross-functional product teams with ambiguous requirements and fast iteration.

Responsibilities

  • Build AI-powered product features end to end, from React/TypeScript user interfaces through Node.js/Python backends, with real-time streaming, graceful degradation, and human-in-the-loop interaction patterns.
  • Translate retrieval-augmented generation pipelines, agent workflows, and structured reasoning into natural interactions for compliance practitioners.
  • Partner with AI engineers to define API contracts and output schemas, and translate AI capabilities into product interactions for compliance practitioners.
  • Advocate for users in technical decisions, identify where model outputs fail in practice, and iterate on the product layer accordingly.
  • Build user-facing feedback loops that capture signal about AI output quality and make it actionable for the broader AI team.
  • Instrument AI features with product-level observability for latency, engagement, task completion, and drop-off, and build integration and end-to-end tests to validate behavior across the full stack.
  • Establish reusable patterns, including streaming hooks, feedback components, and AI state management, to accelerate future AI feature development.
  • Mentor engineers newer to AI product development and participate in design reviews with engineering depth and product judgment.
  • Set standards for how AI features look, feel, and behave across the product, establishing patterns for the product engineering organization.
  • Turn AI capabilities into product interactions that help compliance practitioners work confidently and effectively.
  • Accelerate AI product development by establishing reusable patterns, components, and interfaces.
  • Influence the roadmap through close understanding of both customer experience and AI capabilities.

Desired Qualifications

  • Experience in compliance, security, governance, risk, and compliance, or other document-heavy enterprise domains.
  • Experience with Model Context Protocol or similar tool-use interfaces for AI agents.
  • Exposure to retrieval-augmented generation system design, especially debugging retrieval quality issues from the product layer as a consumer.
  • Experience building feedback and annotation tooling that captures user signal on AI output quality.

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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