Senior AI Engineer

About the role

You will own the design, implementation, and continuous improvement of agentic AI systems that power compliance automation at enterprise scale. You will translate complex regulatory and evidence-based requirements into reliable, production-ready AI workflows that enhance trust and decision-making across the platform. This role requires deep collaboration with product, security, and platform teams to ensure AI capabilities are generalizable, reusable, and safely embedded into core customer workflows. You will drive the architecture of intelligent systems that reason over structured and unstructured data while maintaining strict standards for explainability and auditability. A core part of this role is building automated reasoning over regulations and evidence, enabling scalable and responsible AI use in trust-critical environments. You will create interactive experiences that allow users to engage naturally with complex compliance, risk, and control data through intelligent interfaces. Ultimately, you will be responsible for delivering AI solutions that are not only innovative but also performant, cost-efficient, and aligned with Drata's mission of earning and keeping user trust.

Key facts

What you'll do

Design and implement LLM-powered agentic systems capable of multi-step reasoning, evidence grounding, and decision support for compliance and security workflows.

Develop automated reasoning over regulations, controls, and evidence to support interpretation, alignment, and validation in enterprise contexts.

Architect and deploy scalable LLM and retrieval-based agent systems in production environments while optimizing for latency, cost, and reliability.

Partner with platform, security, product, and application development teams to operationalize AI capabilities safely and effectively across diverse technical environments.

Create interactive AI experiences that allow users to engage naturally with complex compliance, risk, and control data through conversational and reasoning interfaces.

Embed human-in-the-loop workflows, confidence thresholds, and safety guardrails to ensure responsible, transparent, and auditable AI behavior.

Build generalizable AI components and reusable tooling that can be applied across multiple Drata products and compliance domains rather than one-off point solutions.

Ensure AI outputs are traceable, explainable, and auditable to meet the expectations of enterprise customers, internal governance, and external auditors.

Collaborate closely with cross-functional stakeholders to turn evolving compliance requirements and customer needs into robust, production-ready AI solutions.

Continuously evaluate AI system performance, experiment with new techniques, and drive improvements in accuracy, efficiency, and user trust in automated reasoning.

Contribute to technical design reviews, code quality standards, and best practices for AI engineering in a regulated, trust-critical environment.

Work with product managers and domain experts to scope, prototype, and iteratively refine AI features that deliver measurable value to customers.

Requirements

Must have a Bachelor's degree in Computer Science, Engineering, or a related technical field or equivalent practical experience.

Possess 7+ years of hands-on software engineering experience with at least 2 years specifically in ML/AI engineering.

Demonstrate deep proficiency in Python for building production-grade AI systems, including experience with LLMs, retrieval, and agent frameworks.

Show a strong track record of designing and deploying scalable, reliable, and secure AI/ML systems in production environments.

Have substantial experience with modern LLM APIs, model fine-tuning or adaptation techniques, and prompt and chain-of-thought engineering for complex tasks.

Demonstrate expertise in building retrieval-augmented systems, tool use, and structured reasoning methods that support explainable and auditable AI.

Possess strong knowledge of software engineering best practices, including version control, testing, code review, and CI/CD specific to AI pipelines and model lifecycle management.

Be comfortable working in a fast-paced, mission-driven environment where priorities evolve quickly and systems must scale under enterprise trust requirements.

Nice to have

Experience with compliance, risk, or security domains and familiarity with common frameworks, standards, or regulations in these areas.

Background in building or deploying agentic workflows, including orchestration, tool integration, and human oversight patterns.

Contributions to open-source AI/ML projects or a portfolio of production AI systems demonstrating impact at scale.

Practical notes

This role is full-time and remote within the United States. The position may involve occasional travel for team in-person gatherings, and candidates must be eligible to work in the U.S. without sponsorship at this time.