Regional Vice President - EMEA (London)

Overview

You run the London-based sales team for WRITER's EMEA region, selling an enterprise AI platform to F500 and G2000 organizations. You manage a team of AEs (likely 5-10 based on the "exceptionally high-performing team" language), run weekly forecast calls, work strategic deals alongside your reps, and spend significant time hiring to scale the region. The product is an AI platform with agents, LLMs, and knowledge graph capabilities - complex enough that deals involve IT, security, procurement, and business stakeholders.

Role Snapshot

Company Context

Stage: Late-stage (2,400+ employees suggests Series D+ or pre-IPO)

Size: 2,417 employees globally

Growth: Actively scaling EMEA with established US customer base (Vanguard, Salesforce, Uber)

Market Position: Competing in the crowded enterprise AI platform space -Category is hot but getting noisy with competitors ranging from OpenAI Enterprise to Anthropic Claude for Enterprise to established players like Microsoft adding AI capabilities

GTM Reality

Pipeline Sources:

• 20-30% Inbound - mostly US-based marketing that occasionally surfaces EMEA leads; quality varies because content is often US-centric
• 60-70% Outbound - your team is building territory plans, targeting specific F500/G2000 accounts, and running multi-threaded outreach campaigns
• 10-20% Partner/Referrals - some introductions from existing customer network and SI partners

SDR/AE Structure: Likely dedicated BDRs for enterprise prospecting, but AEs still do significant relationship development at VP+ level

SE Support: Shared SE pool - you'll compete for SE time on big demos and POCs with other regions

Competitive Landscape

Main Competitors:

• Hyperscalers adding AI (Microsoft Copilot, Google Vertex AI)
• Pure-play AI platforms (Scale AI, Cohere for Enterprise)
• LLM providers going direct (OpenAI Enterprise, Anthropic)
• Established enterprise software adding AI features

How They Differentiate: Enterprise-first build with governance, security, and IT-friendliness as core features; Knowledge Graph for company-specific context; Palmyra LLMs positioned as alternative to OpenAI dependency

Common Objections:

• "We're already using Microsoft/Google for AI"
• "Our data science team is building this internally"
• "We're waiting to see how the AI landscape settles before committing"
• "OpenAI/Anthropic is the market leader for LLMs"

Win Themes:

• Enterprise governance and security baked in from day one
• Knowledge Graph enables company-specific AI vs generic chatbots
• Avoid single-vendor lock-in to OpenAI
• Faster deployment than internal build

What You'll Actually Do

Time Breakdown

Team Management (35%) | Strategic Deals (30%) | Hiring/Recruiting (20%) | Internal Ops (15%)

Key Activities

• Weekly forecast scrubs: You're running 1:1s with each AE, reviewing their top 10-15 deals, pushing them on commit vs pipeline, and figuring out which deals are real and which are slipping. This takes 8-10 hours per week when done properly.

• Working strategic accounts yourself: You're in the room for the largest opportunities - building relationships with CIOs and Chief AI Officers, aligning with the US-based executive team on account strategy, and closing deals your AEs can't get over the line alone. Expect 2-3 active strategic accounts at any time.

• Hiring and scaling the team: EMEA is growing, which means you're spending 5-10 hours per week on recruiter syncs, candidate interviews, reference checks, and offer negotiations. The "world-class" language in the post suggests they have high hiring bars and you'll pass on most candidates.

• Monthly/Quarterly business reviews with EMEA leadership: You're presenting your forecast, explaining gaps to plan, defending your hiring requests, and getting grilled on why deals slipped. Darragh (your boss) wants visibility into everything.

• Coaching deal strategy: Your AEs bring you into stalled deals or complex multi-stakeholder situations. You're helping them navigate IT security reviews, align multiple buyer groups, or reframe the business case when they're stuck on price.

• Internal advocacy: You're constantly fighting for EMEA priorities - getting product to support European data residency requirements, lobbying for SE headcount in London, asking marketing to run events in your territory, and coordinating with the US team when they try to poach your accounts.

The Honest Reality

What's Hard

• The AI market is chaotic right now: Every enterprise has 5-10 vendors pitching AI solutions. Buyers are confused, cautious, and often waiting to see how things shake out. Your deals will stall in "evaluation" for months because nobody wants to make the wrong bet.

• EMEA is always secondary to US: Product features ship for US requirements first. Marketing budgets favor US events. The best SEs are in the Bay Area. You'll spend energy fighting to get EMEA the resources it needs.

• You're managing experienced AEs who don't want to be micromanaged: The "high-performing team" language means these aren't junior reps. They know how to sell and will push back if you try to over-manage. Your job is to clear blockers and help on strategic deals, not tell them how to run discovery calls.

• F500 procurement is brutal: Deals that should close in Q3 slip to Q4, then Q1, then stall in legal. Security reviews take 8 weeks. IT wants a POC with their specific use case. Procurement wants a 15% discount even though you're already at the floor. You'll have $2M in pipeline that's been "90% commit" for two quarters.

What Success Looks Like

• You hit 90-100% of team quota consistently, even when half your pipeline slips each quarter because you've learned to over-forecast
• Your team retention is strong - people want to work for you because you remove obstacles and protect them from internal chaos
• You close 2-3 strategic logo deals per year that become reference accounts for the rest of EMEA
• Your hiring pipeline is full enough that when someone leaves or you get headcount, you can move fast

Who You're Selling To

Primary Buyers:

• Chief AI Officers / Head of AI (where they exist - newer role)
• CIOs and CTOs (IT owns enterprise platform decisions)
• Chief Data Officers (care about knowledge graph and data governance)
• VPs of Engineering or Product (end users of the platform)

What They Care About:

• Data security and governance: Can they use this without exposing sensitive company data? What happens to data sent to LLMs? How do they enforce policies?
• Integration with existing stack: Does it work with their Salesforce, ServiceNow, Slack, Microsoft stack? Do they need to rip and replace anything?
• ROI and measurable outcomes: Prove this isn't just an expensive experiment. Show productivity gains, cost savings, or revenue impact from existing customers.
• Vendor stability: Is WRITER going to be around in 3 years or will they get acquired/run out of money? Can they support a global F500 deployment?

Requirements

• 10+ years enterprise software sales experience with at least 5 years managing sales teams (this isn't a first-time manager role)
• Track record selling complex platform deals into F500/G2000 - you need to understand how IT, security, procurement, and business buyers interact
• Experience scaling a sales team in EMEA - you've hired AEs before, built comp plans, run forecasts
• Comfortable being hands-on - you'll carry a number yourself and work deals, not just manage from the sidelines
• Based in or willing to relocate to London - EMEA leadership is building the team there and you need to be in-market
• Proven ability to thrive in fast-moving environments - the AI market is changing monthly and you can't wait for perfect process