Product Marketing - Maya Enterprise

The company

WORK-SELF builds Maya Enterprise, the Human Context infrastructure for enterprise AI. AI agents increasingly perform work inside large organisations, but they need context about the people and decisions around that work: who owns it, which decisions an agent can make, when a person reviews the result and how exceptions are escalated. Maya provides this governed context through an MCP-native server so employees and agents can complete work through accountable workflows.

We are a London-based enterprise AI company. In our first year we won enterprise contracts across banking, utilities, property services and European public finance, reached EBITDA-positive operations with a small team, and deployed Maya with enterprise customers. We work with technology and delivery partners and hold a granted US AI patent assigned to the company. Our next stage is scaling product delivery, enterprise adoption and partner-led growth. The people joining now will help build that next stage.

The role

You will own how Maya Enterprise is positioned and brought to market: which enterprise segments to enter first, which buying problems justify investment, how our product differs from alternatives, and how customers, sales teams and partners understand the offer. You will shape market strategy, pricing and packaging recommendations, customer proof and repeatable sales playbooks. The Founding Product Lead owns development of Maya; you own market understanding and commercial readiness.
Expected compensation ranges: £40k – £55k per year (Base) + £80k - £145k (Equity) + Bonus on performance and standard benefits

What you will own

• Markets, buying groups and customer evidence. Identify the highest-priority enterprise verticals, budget owners, operational sponsors and adoption triggers. Interview buyers and study win/loss evidence to learn what makes Maya necessary rather than merely interesting.

• Category positioning and accurate differentiation. Explain Maya's Human Context role alongside agent platforms, workflow orchestration, workforce AI, context/data platforms and governance products. Maintain clear competitive analysis distinguishing direct substitutes, complementary infrastructure and potential partners; do not imply an unconfirmed partnership.

• Product proof and sales enablement. Translate capabilities into vertical use cases, ROI models, battlecards, executive decks, objection responses, pricing explanations and partner material. Use verifiable customer evidence and approved product claims.

• GTM, offers and packaging. Recommend vertical entry strategies, pilot-to-production offers, packaging and pricing approaches with the founder and sales team. Equip distribution partners and commercial teams to run repeatable discovery and launch motions.

• Market learning and adoption. Track buying behaviour, expansion signals, competitor moves and adoption objections. Feed customer problems to the product team without taking ownership of technical development or release delivery.

You will know you are succeeding when

• First 30 days. You have defined priority buyers, their purchasing problems and gaps in Maya's current positioning. Working with sales, you have established a plan to build qualified pipeline coverage towards 10 times the revenue target.

• By 90 days. Sales and partner teams have differentiated buyer messaging, vertical use cases, competitive guidance and evidence-backed pilot and packaging offers. You maintain an approved product-claims register and documented points of differentiation against relevant competitors.

• By 180 days. You use customer wins, losses and adoption evidence to improve repeatable sector go-to-market plays and sales conversion. You maintain a win-loss register and target a 70–80% win rate in comparable competitive opportunities, with the sample and qualification criteria clearly recorded.

Who does well here

• Experience marketing complex B2B SaaS, enterprise infrastructure, workflow or AI products to senior buyers.

• Excellent positioning, narrative development, research and executive-standard writing.

• Comfort with product architecture and the ability to make technical differentiation understandable without overstating claims.

• Proven market segmentation, buyer interviews, competitive intelligence, positioning, packaging and enterprise sales enablement experience.

• Commercial judgement about purchasing decisions, proof, pricing and adoption; close collaboration with product and sales.

Content is one output of this role. Customer research, commercial positioning and buying evidence drive the work.

What you get

• Ownership of the market story for an emerging enterprise AI infrastructure category.

• Direct access to founders, product builders, sales teams and enterprise feedback.

• The opportunity to help build and scale an early-stage enterprise AI company.

If this resonates with you, we would love to hear from you. Any questions, please email us at careers@work-self.com