Staff AI Engineer

Job Summary:

At Drata, we’re rethinking how compliance gets done, and AI is a core part of that. We’re looking for a Staff AI Engineer to help shape how intelligent systems power trust-critical enterprise workflows.

This isn’t a “build a feature and move on” role. You’ll help define how AI is architected across the company. You’ll make foundational decisions about what we build, how we measure quality, and where we invest. From early research to production deployment, you’ll own systems end-to-end, and your judgment will directly influence our technical direction.

You’ll work at the intersection of LLMs, retrieval systems, agentic workflows, and real-world compliance challenges, partnering closely with product, platform, and security teams to build AI that’s powerful, reliable, and responsible.

What you’ll Do:

Shape the Architecture
Design and own production AI systems end-to-end (LLM pipelines, RAG, reranking, vector stores, orchestration).

Make thoughtful build/don’t-build decisions based on real data.

Evolve our AI stack over time, from model infrastructure to workflow orchestration to evaluation tooling.

Raise the Quality Bar
Design evaluation systems that measure retrieval quality, reasoning accuracy, end-to-end performance.

Build tooling that helps the team iterate confidently and catch regressions early.

Define how we measure success across the platform.

Investigate Deeply & Decide with Evidence
Analyze production outputs to identify failure patterns and root causes.

Turn complex findings into clear technical recommendations.

Know when to push forward and when to pause based on data.

Lead Across Teams
Be the go-to technical voice for AI architecture decisions.

Influence standards for how LLM systems are built, tested, deployed, and monitored.

Mentor senior engineers through design reviews and hands-on collaboration.

Partner with product and compliance teams to translate domain complexity into clean technical solutions.

Build Responsible, Production-Ready AI
Ship systems optimized for latency, cost, reliability, and auditability.

Embed safety guardrails, confidence thresholds, and human-in-the-loop workflows.

Ensure outputs are traceable and explainable.

What you’ll bring:

10+ years of software engineering experience, including 3+ years working directly on ML/AI systems.

Real ownership of production LLM systems.

Deep experience with RAG, embeddings, reranking, vector databases (Pinecone, FAISS, Chroma, etc.), and agentic workflows.

Experience designing evaluation frameworks and using quantitative analysis to improve system performance.

Strong Python skills (TypeScript is a plus).

A track record of making architectural decisions that shape team direction.

Experience operating AI systems in production - observability, reliability, cost tradeoffs.

The ability to break down ambiguous, high-stakes problems into structured investigations.

Clear communication skills and comfort working cross-functionally.

Nice to have:

Experience in compliance, security, or other regulated domains.

Familiarity with enterprise data platforms or Snowflake-based analytics.

Experience with orchestration systems like Temporal or Airflow.

Experience building or using LLM evaluation platforms (e.g., Braintrust).

Contributions to technical communities or published work.

Why this role matters:

You won’t just ship features - you’ll help define how AI is built at Drata.

Your work will:

Set the architectural foundation for our AI systems.

Establish the quality bar that lets us move fast with confidence.

Ensure our technical investments are grounded in evidence.

Raise the technical bar across the AI organization.

This role will receive a competitive base salary, benefits, and stock, typically in the form of Restricted Stock Units (RSUs). The applicable salary range for this role is: $200,700 - $271,500, subject to change.

Tier 1: $220,800 - $298,800

Tier 2: $198,700 - $268,900

Tier 3: $176,600 - $239,000

You can view which tier applies to where you plan to work here. A variety of factors are considered when determining someone’s leveling and compensation–including a candidate’s professional background and experience. These ranges may be modified in the future and final offer amounts may vary from the amounts listed above.