6 months ago
Base Salary
$201k - $272k/yr
Responsibilities
- Design and own production AI systems end-to-end, including LLM pipelines, RAG, reranking, vector stores, and orchestration.
- Make build-versus-buy decisions and evolve the AI stack across model infrastructure, workflow orchestration, and evaluation tooling.
- Design evaluation systems for retrieval quality, reasoning accuracy, and end-to-end performance.
- Build tools to support iteration and detect regressions.
- Analyze production outputs, identify failure patterns and root causes, and make evidence-based technical recommendations.
- Act as the primary technical voice for AI architecture decisions and influence standards for building, testing, deploying, and monitoring LLM systems.
- Mentor senior engineers through design reviews and hands-on collaboration.
- Partner with product and compliance teams to translate domain complexity into technical solutions.
- Ship AI systems optimized for latency, cost, reliability, and auditability with safety guardrails, confidence thresholds, human-in-the-loop workflows, traceability, and explainability.
Requirements
- 10+ years of software engineering experience, including 3+ years working directly on ML/AI systems.
- Hands-on ownership of production LLM systems.
- Deep experience with RAG, embeddings, reranking, vector databases, and agentic workflows.
- Experience designing evaluation frameworks and applying quantitative analysis to improve system performance.
- Strong Python skills; TypeScript is a plus.
- Experience making architectural decisions that shape team direction.
- Experience operating AI systems in production, including observability, reliability, and cost tradeoffs.
- Ability to investigate ambiguous, high-stakes problems and communicate clear technical recommendations.
- Clear communication skills and comfort working cross-functionally.
- Experience in compliance, security, or other regulated domains is preferred.
- Familiarity with enterprise data platforms or Snowflake-based analytics is preferred.
- Experience with Temporal or Airflow is preferred.
- Experience building or using LLM evaluation platforms such as Braintrust is preferred.
- Contributions to technical communities or published work are preferred.
Benefits
- Hybrid work from the San Francisco office, with consideration for remote candidates across the U.S.
- Stock equity in the form of Restricted Stock Units (RSUs).
- Up to 100% employer-paid medical, dental, and vision premiums for employees and dependents.
- Wellness benefits and healthcare concierge services.
- 401(k), company-paid life and disability insurance, tax-advantaged spending accounts, and discounted voluntary benefits.
- Paid parental leave after six months, plus Kindbody fertility and family-building benefits and leave specialists.
- Annual professional and personal development stipends and internal learning opportunities.
- Flexible vacation policy and paid holidays.
Tech Stack
Categories
About Drata
Drata provides the trust network that enables businesses to operate, scale, and partner with confidence. Powered by AI and designed to operationalize trust, the Drata Agentic Trust Management Platform continuously interprets controls, risk, and assurance signals—reducing repetitive manual work while improving visibility into internal and third-party risk, enabling always-on audit readiness across compliance frameworks, and accelerating security reviews. Purpose-built for enterprise complexity, Drata unifies governance, risk, compliance, and assurance to deliver faster time-to-value, reduce operational overhead, and enable continuous trust for 8,000+ organizations worldwide.