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Snowflake is seeking a Senior Director of Applications Engineering to lead the transformation of enterprise operations across Finance, HR, and Legal domains. This role sits at the intersection of product strategy, engineering leadership, and AI innovation, tasked with redesigning legacy workflows into AI-native, software-defined products that deliver measurable business impact.
You will define and execute a multi-year product and engineering roadmap, partnering directly with C-level executives (CFO, HR, Legal) to challenge existing processes and architect future-state operating models. Your mission is to move beyond incremental feature development to build intelligent agents and autonomous workflows that understand context, act across enterprise systems, operate within governance guardrails, and escalate to humans when judgment is required.
Key responsibilities include establishing a product-led operating model where business and technology co-own strategy, adoption, reliability, and value realization. You will define software architecture and engineering standards for AI products—covering orchestration, context retrieval, tool integration, safety, compliance, latency, and cost optimization. You'll build reusable AI patterns and modular platforms to enable rapid deployment of agentic capabilities across the organization without bespoke engineering for each use case.
Leadership scope is substantial: you will hire, mentor, and scale a world-class product and engineering team with strong AI fluency and operational excellence. You'll lead cross-functional product pods accountable for adoption metrics, workflow completion rates, and measurable ROI. You'll also ensure all AI implementations maintain rigorous governance, auditability, SOX controls, data privacy, and security standards.
Ideal candidates bring 15+ years in enterprise technology, product, or engineering, with 5+ years leading multi-disciplinary organizations at Director level or above. You should have a proven track record building and scaling software-defined, AI-native products in production with measurable business impact. Strong technical grounding in modern AI architectures (LLM/agent patterns, orchestration, tools, evaluation) and cloud data platforms like Snowflake is essential. You combine first-principles product thinking with executive presence, deep compliance and audit knowledge, and the ability to move rapidly from ambiguity to working product.
