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Partner Manager

Wordsmith
CompanyWordsmith
CategoryOperations & Admin
LocationLondon
RemoteHybrid
EmploymentNot stated
LevelManager
SalaryNot stated by the employer
Posted10 Jul 2026
Last verified30 Jul 2026
SourceEmployer career page (ashby)
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Description
Partner Manager London Wordsmith Wordsmith is building the AI-enabled command centre for in-house legal teams. Our SI and consulting partners play a critical role in helping customers implement, customise, and get the most value out of the platform. We're looking for someone to build and scale the partner relationships that make that possible. The Role Partner Managers develop and manage Wordsmith's strategic referral partners. Based from our London office, you'll build deep, commercially impactful relationships with SI and consulting partners who support our customers through implementation, delivery, and ongoing adoption of the Wordsmith AI platform. You'll also manage a number of strategic ISV referral partners. You'll drive co-sell motions, identify joint account opportunities, and make sure partners are fully enabled to deliver great customer outcomes. This is a highly relationship-driven role that sits at the heart of our go-to-market strategy. What You'll Do Co-Sell Strategy & Account Planning - Develop and execute co-sell motions with SI and consulting partners, identifying joint target accounts and driving coordinated sales efforts to accelerate pipeline and close deals. - Run regular account mapping sessions with partners to identify overlapping opportunities, whitespace, and mutual accounts for joint pursuit. - Own partner-influenced and partner-sourced pipeline reporting, tracking co-sell contribution to quarterly and annual revenue targets. Partner Enablement & Delivery - Ensure SI partners are fully trained and certified on the Wordsmith AI platform, equipping them to lead implementation, customisation, and delivery engagements. - Work closely with partners to ensure high-quality implementation and delivery for joint customers, acting as an escalation point and quality assurance layer. Relationship Management & Recruitment - Build and maintain strong executive and practitioner-level relationships across SI partner organisations, conducting regular business reviews and strategic planning sessions. - Identify, evaluate, and onboard new SI and consulting partners that align with our target market segments and customer needs. Commercial Governance - Manage partner agreements, deal registration, and commercial frameworks to ensure clear rules of engagement and mutual accountability. Cross-Functional Collaboration - Work closely with Sales, Customer Success, and Product teams to align on partner-driven opportunities and ensure seamless customer experiences. What we're looking for Essential - 3–6 years of experience in channel partnerships, SI/consulting alliances, or partner management within a SaaS or enterprise technology company. - Proven track record of driving co-sell motions and generating partner-influenced pipeline and revenue. - Strong experience with account mapping, joint account planning, and coordinated selling with partners. - Deep understanding of the SI and consulting partner landscape, including how professional services firms operate and make decisions. - Excellent relationship management skills, with the ability to build trust and credibility at both executive and practitioner levels. - Commercial negotiation skills, with experience managing partner agreements and deal registration processes. - Strong communication and presentation skills, comfortable leading QBRs, partner enablement sessions, and executive briefings. - Self-motivated, organised, and able to manage multiple partner relationships and priorities simultaneously. Valued - Experience working in or with the legal technology or legal services industry. - Existing relationships with consulting firms, legal operations consultancies, or Big Four/mid-tier advisory practices. - Familiarity with partner relationship management tools (e.g. Crossbeam, Reveal, Salesforce PRM). - Understanding of AI/ML products and how they're implemented in enterprise environments. Why this
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