Director, Applied Field Engineering – AI/ML Product Specialist
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Job Description
Director of Applied Field Engineering leading specialized teams in AI/ML product deployment at Snowflake. Overseeing technical sales excellence and shaping product direction within a collaborative culture.
Responsibilities:
- Drive Consumption Activation: Shift beyond the 'technical win' to ensure customers successfully move workloads into production, directly accelerating the realization of contracted credits.
- Optimize Technical Sales Cycles: Refine engagement models to ensure AFEs are deployed on high-impact opportunities that maximize both TACV (Total Annual Contract Value) and immediate consumption potential.
- Architect for Scale: Ensure architectures are optimized for long-term growth and business value, preventing technical debt that could stall future consumption.
- Identify Product Gaps: Act as a critical feedback loop between the field and Product Engineering; systematically identify, document, and advocate for features or fixes required to unlock blocked workloads.
- Shape Product Direction: Partner with Product Management to influence the roadmap based on emerging AI/ML trends and 'boots on the ground' customer requirements.
- Recruit, hire, and manage a high-performing team of Applied Field Engineers (AFEs), prioritizing their ongoing development and performance management.
Requirements:
- 15+ years of industry experience in a pre-sales, technical sales, or technical consulting capacity.
- 4+ years of people management experience, preferably leading specialized technical overlay teams.
- Proven track record in Consumption-based models: Experience driving not just 'bookings,' but the actual activation and usage of software services.
- Strategic Product Influence: Demonstrated ability to translate complex customer challenges into actionable product requirements and influence engineering roadmaps.
- Deep Technical Authority: Executive-level expertise in at least two of the following: GenAI/LLMs, Machine Learning, Data Engineering, or Cloud Data Architecture.
- Executive Presence: Proven ability to advise C-level executives on future-state technical architectures and the business ROI of AI/ML investments.
- Education: University degree in computer science, engineering, mathematics, or related fields (or equivalent experience).
Benefits:
- Health insurance
- Professional development opportunities
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