Staff Applied AI Scientist

As a Staff Applied AI Scientist, you will design, build, and scale production GenAI applications across Sequoia's People Platform. You will work on AI-powered assistants, retrieval and reasoning systems, agentic workflows, document intelligence, decision-support experiences, and automation capabilities that improve productivity, service quality, client experience, and business outcomes. This is a hands-on technical leadership role for someone who has moved beyond prototypes. You should have experience taking GenAI applications through the last mile into production, including evaluation, observability, reliability, cost optimization, security, user trust, and measurable impact. You will partner closely with Product, Engineering, Design, Security, Compliance, Operations, and business stakeholders to identify high-impact AI opportunities, make pragmatic architecture decisions, and ship trustworthy AI experiences that work at real-world scale.

The core responsibilities for the job include the following:

Build for Customer Impact and Experience:

• Design, build, and launch GenAI-powered experiences across Sequoia's People Platform, including assistants, copilots, document intelligence, workflow automation, and decision-support capabilities.
• Identify high-impact opportunities where AI can improve productivity, service quality, operational efficiency, client experience, or revenue outcomes.
• Take AI applications from idea to production, partnering with Product, Engineering,
• Design, Security, and business teams to define the right problem, ship usable solutions, and measure real-world impact.

Build for Enterprise Quality and Scale:

• Architect reliable GenAI systems using modern patterns such as RAG, agentic workflows, tool use, structured outputs, fine-tuning where appropriate, and strong grounding in enterprise knowledge.
• Define practical evaluation and quality frameworks to measure accuracy, relevance, groundedness, safety, latency, cost, user trust, and business impact.
• Build for production realities, including observability, monitoring, versioning, fallback paths, privacy, and operational ownership.
• Stay current with the rapidly evolving AI ecosystem and apply new techniques pragmatically where they improve quality, speed, or cost-effectiveness.
• We are especially interested in candidates who have experienced the practical realities of operating enterprise-grade GenAI applications in production. Prototype-only experience is not sufficient for this role.

Requirements:

• 8+ years of experience building applied AI/ML-based intelligent software systems.
• 2+ years of practical GenAI application experience, including at least one production GenAI application used by real users at meaningful scale.
• Proven experience taking GenAI applications beyond PoC into production, with clear ownership of launch quality, reliability, cost, user feedback, adoption, and measurable impact.
• Strong judgment in designing LLM applications using the right mix of RAG, agents, tool use, structured outputs, orchestration, retrieval, grounding, frontier models, open-source models, fine-tuning, smaller task-specific models, and deterministic systems.
• Experience defining practical evaluation approaches for GenAI applications using methods and tools such as LangFuse, Arize, or similar.
• Fluency with modern AI application frameworks and LLMOps tooling such as LangGraph, LangChain, LlamaIndex, and GPT/Claude/Gemini APIs.
• Prefer coding with AI-native development tools such as Cursor, Claude Code, or similar, with the ability to move fast while maintaining quality, security, and trust in production systems.
• Bonus: experience with advanced AI techniques such as GraphRAG, long-context architectures, model routing, caching, cascades, PEFT/LoRA/QLoRA, distillation, or open-source model deployment.