Director AI Solutions, EMEA-LATAM

Job Summary

NetApp sits on 60% of the world's unstructured data. AI runs on unstructured data, and our customers' data is already with us, so we start most AI conversations from a position nobody else has.

We are building the engine that turns that into business, and both halves of it are already here: Solution Architects who design the data infrastructure for training, inference, agent runtimes and AI-ready data lakes, and business development people who build the propositions and target lists that open those conversations. What we want now is to run them as one team, with one plan, going after the AI opportunity in EMEA/LATAM proactively rather than one deal at a time.

That is this role. You lead the AI Solution Architects and the AI business development / GTM profiles across EMEA/LATAM, and you are accountable for a commercial result: incremental AI pipeline, a better win rate, and AI bookings growth year over year.

Key Responsibilities

Build the value propositions with the teams who have to sell them

Own our AI value propositions across the four workloads, built together with your architects and business developers, Area sales, Marketing and the partners we sell with. Each one needs an architecture we can defend, the accounts it applies to, and the competitive position and proof points the field will be asked for.

Scale what works

Take a proposition that produces opportunities in one country and make it work across the region, run by people who did not build it. Stop the motions that do not convert. Scale through partners as well, particularly where the buying decision follows a validated reference architecture.

Be our AI voice in EMEA

Be the person the market, the press and our own field look to for NetApp's view on AI data infrastructure: inference economics, agent runtimes and data governance, European sovereignty and regulation, and the competitive stacks. Build the same standing in the people around you.

Hire and develop the talent this depends on

Hire above the bar we have today across two quite different profiles, set the AI technical bar for the wider SE and SA community, build succession, and choose deliberately where the team spends its time.

Make our SEs and Client Executives effective on AI workloads

Get several hundred Systems Engineers and Client Executives to the point where they can open, qualify and lead an AI workload conversation on their own accounts. Judge the enablement on the opportunities they create afterwards.

Build the relationships where platform decisions get made

Hold your own relationships with the CTOs, chief architects and heads of AI and platform who decide where their AI workloads will run, maintained between deals, so we are in the conversation before the architecture is set.

Job Requirements

Basic qualifications

• 12+ years in enterprise technology including strategic and people leadership, with 5+ years managing people. Experience leading both technical (pre-sales, solution architecture) and commercial (business development, GTM) profiles, or a credible case for why you can.
• A record of creating pipeline in a new or emerging segment, with the numbers and the plays behind it.
• Real fluency in the AI infrastructure stack, deep enough to set a bar rather than repeat one: GPU clusters and reference architectures, training and fine-tuning pipelines, inference serving and its economics, agent runtimes and frameworks, RAG and vector search, data lake architecture, and where the data layer sits in each. You should be able to hold your own with a CTO or Head of AI without an architect in the room.
• Commercial and dimensioning judgement: able to test whether a solution is right-sized and defend a design choice, including a smaller one, under pressure.
• Able to influence without authority across sales, technical, marketing and partner organisations in a matrixed, multi-country environment.
• Executive presence at C-level, including when the outcome is uncertain.
• Fluent English and willing to travel across EMEA/LATAM.

Preferred qualifications

• Relationships in the European AI ecosystem - sovereign AI programmes, neoclouds, AI ISVs, GPU vendors, integrators, AI investors.
• Experience building a GTM motion from scratch, and the team that runs it.
• Understanding of EU AI and data sovereignty regulation, including public-sector procurement.
• Experience with hyperscalers and partner-led sales models.
• A storage or data infrastructure background helps but is not required. If you come from storage, show us AI deals you have been in and a current read on the market.
• Another European language.

Day in a Life

You start on the inference proposition with two architects, a business developer and an SE manager, arguing about whether the cost-of-serving case holds up with a customer who already has GPUs. Mid-morning, the head of platform at a large European bank, on their AI roadmap rather than on anything of ours. Before lunch, the architecture review on our largest inferencing deal, where you push back on a design that won't survive the customer's second model. Afternoon is a deal clinic with a dozen SEs and CEs taking the new proposition into their own accounts next week. Then an analyst briefing, and half an hour reworking the proposition because last quarter's three losses all turned on the same objection.