Product Manager (AI-First)
GEEIQ
Software Engineering, Product, Data Science
London, UK
Posted on May 1, 2026
About Us
We are a fast-growing Series A SaaS startup at the forefront of the next big shift in marketing—transforming the way brands connect with audiences in virtual worlds. This is a shift on par with the rise of social media, and we are building the analytics engine to power it. You will be joining a tight-knit, high-impact team of 40 people (including a product team of 3 and an engineering team of 10), meaning your work will directly shape the trajectory of our platform and company.
We are a fast-growing Series A SaaS startup at the forefront of the next big shift in marketing—transforming the way brands connect with audiences in virtual worlds. This is a shift on par with the rise of social media, and we are building the analytics engine to power it. You will be joining a tight-knit, high-impact team of 40 people (including a product team of 3 and an engineering team of 10), meaning your work will directly shape the trajectory of our platform and company.
About the Role
As a Product Manager, you will play a pivotal role in shaping the direction of our marketing analytics platform. We are looking for an AI-first product thinker, someone who understands how to bridge the gap between complex virtual world data, cutting-edge AI capabilities, and human-centric workflows.
You will work closely with our lean engineering and design teams to deliver impactful solutions. You won't just ship features; you will deliver measurable outcomes, taking ownership of the product development lifecycle from ideation to launch while bringing a "get it done" mentality to our fast-paced environment.
- Application Deadline
- May 31, 2026
- Department
- Product
- Employment Type
- Permanent - Full Time
- Location
- London
- Workplace type
- Onsite
Key Responsibilities
- Own the Vision & Roadmap: Define product features in alignment with company goals, customer needs, and market trends. Use your intuition and data to make hard trade-offs between what unblocks our customers today and what enables their success tomorrow.
- Ship AI-Native Products: Own the lifecycle of AI-enhanced experiences. Envision and prototype intelligent features, always ensuring human-in-the-loop controls, clear boundaries of authority, and safe, auditable behaviors.
- Evaluate AI Flows Rigorously: Partner with engineering to test and measure AI helpfulness, accuracy, and safety, accounting for real-world complexities in marketing analytics data.
- Co-Create with Customers: Talk to customers, sales, and client services teams weekly. Build rapid feedback loops to deeply understand user workflows, JTBD (Jobs to Be Done), and pain points.
- Cross-Functional Collaboration: Lead cross-functional cycles with urgency and agency. Work tightly with your engineering (backend and frontend) and design counterparts to ensure user-centric design, scalability, and technical feasibility.
- Agile Execution & Autonomy: Lead product development cycles using agile methodologies. Do the simple thing first to validate your hypothesis, manage backlogs, and prioritize initiatives to balance short-term needs with our long-term vision.
- Data Analysis & Metrics: Define north-star and guardrail metrics. Analyze both qualitative and quantitative data to make data-informed prioritization decisions and refine product offerings.
What we're looking for
- Experience: 5–10 years of experience in product management, ideally in a B2B Martech, SaaS or tech-focused startup environment. You have a track record of shipping high-quality, delightful products.
- AI Product Fluency: Experience defining user problems suited for Generative AI, collaborating on models or heuristics, and establishing evaluation approaches for quality and accuracy. You actively leverage AI to solve user problems and continuously improve your own craft.
- Ability to Write Persuasively: You write strategy memos that align the team, product specs that empower our engineers, and communication that brings stakeholders along. You value clarity over fluff.
- Basic Technical Fluency: You can seamlessly engage with an engineering team of 10 on integration constraints, data contracts, and system trade-offs—no coding required.
- High Standards for Craft: You care about the user journey and edge cases. You move with urgency and take pride in shipping great products.
- A "Get It Done" Mentality: You have a strong bias for action. You are comfortable operating in the ambiguity of a Series A startup and are willing to roll up your sleeves to move projects forward.
Bonus Points
-
Experience working in marketing-related SaaS products, virtual environments or gaming. - Familiarity with tools such as Linear, Notion, or similar agile project management tools.
-
Can point to side projects or proof of work that showcases your bias for action and AI curiosity.
Why join us?
- Join a business at the forefront of the next big shift in marketing.
- Be part of a fast-growing startup with a collaborative, innovative, and supportive team.
- Work on cutting-edge products that are helping top brands navigate the virtual world.
- Opportunity to make a massive, tangible impact on product
- We offer 25 days holiday as standard, with a bonus annual GEEIQ Day to use any time you choose.
- We also have a thriving company culture, with regular socials and lots of fun team events like quizzes, sports days, Hackathons and Bake Offs!
About GEEIQ
Go Virtual with GEEIQ - we’re the data platform helping brands like Walmart, Gucci, L’Oréal and Porsche navigate, measure and grow across virtual worlds. Think Ralph Lauren in Fortnite or Elton John in Roblox, that’s where we come in.
Based in London, our 40-person team combines platform data and human expertise to help the world’s biggest brands navigate this new marketing frontier. We believe the metaverse hype is over; brands now demand measurement, attribution and real ROI. That’s what we deliver.
Every idea is valued here - we’re collaborative, curious and ambitious, shaping how brands Go Virtual with confidence.
Our Hiring Process
Stage 1:
Applied
Stage 2:
Review
Stage 3:
Talent Screening - Interview
Stage 4:
Onsite Interview
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