At a Glance
- Tasks: Lead AI product development from concept to market launch, driving innovation and commercial success.
- Company: Join ZILO™, a pioneering UK FinTech transforming asset management with AI technology.
- Benefits: Enjoy 38 days leave, private healthcare, flexible working, and share options.
- Other info: Dynamic hybrid work environment with opportunities for continuous learning and growth.
- Why this job: Shape the future of AI in finance and make a real-world impact.
- Qualifications: 5+ years in product management with experience in Generative AI and fintech.
The predicted salary is between 63000 - 77000 £ per year.
- About ZILO
- Join the Future of Technology with ZILO™
At ZILO™, we're redefining what's possible in technology.
ZILO™ is the UK-based Fin Tech specialising in global asset and wealth management software, designed to scale and transform businesses of all types using our own developed AI Technology.
Our mission is to digitalise the future of the global asset management industry.
We are a team of experts with decades of combined experience at leading firms globally, who thrive in fast-paced environments and want to shape the future of technology.
Every individual plays a key role in driving progress and making a real impact.
We continuously strive to innovate and improve.
Why work with us?
At ZILO™, you'll be part of a dynamic and inclusive environment where creativity thrives.
We offer the opportunity to work on cutting-edge technology, collaborate with talented individuals, and contribute to projects that have a real-world impact.
We value continuous learning, personal growth, and providing our team with the resources they need to succeed.
Ready to shape the future? Let's talk.
This role is hybrid and there is an expectation of 2-3 days in the London office per week.
About the role
As AI Product Manager you will own ZILO’s AI products from concept through to market launch and commercial success.
You will build products with Generative AI at their core that solve real challenges for ZILO’s clients, improve how ZILO operates, and that our Sales teams can sell with confidence.
You will work with the AI Research, Data and Software Engineering teams to turn emerging capabilities, including Generative AI, large and small language models (LLMs and SLMs) and intelligent workflows, into dependable, compliant, commercially viable products.
You will sit at the intersection of technology, domain expertise, client need and commercial value, bringing the discipline of product management to AI: validating use cases and their commercial potential, setting measurable outcomes, shaping the roadmap and driving delivery through to a successful launch, while making sure the products we ship are accurate, explainable and safe for use in a regulated industry.
We are looking for someone who has done this before: a product manager with real-world experience of taking Generative AI products from idea to live, revenue-generating products, who brings practical knowledge of what it takes to make them work in production and succeed in the market.
Key Responsibilities
- Product Strategy & Roadmap
- Translate ZILO’s AI vision into a clear product strategy and plan, helping to shape and execute it in line with company objectives, market demand and commercial goals.
- Identify and prioritise high-value AI use cases across the ZILO™ platform and asset management operations, such as intelligent automation, data analysis and insight generation, and client-facing and internal tools.
- Develop and maintain the AI product roadmap, prioritising features and enhancements by strategic goals, client impact, feasibility and resource availability.
- Market & Client Insight
- Conduct market research and competitive analysis to identify trends, customer needs and opportunities for AI product development.
- Work closely with Marketing to understand market trends, competitor positioning and target client segments, and to shape clear propositions and messaging for ZILO’s AI products.
- Engage with clients and internal stakeholders to gather feedback, validate concepts and features, and test willingness to adopt and pay.
- Commercial Viability & Go-to-Market
- Build the business case for each AI product, covering target market, value proposition, pricing and packaging, revenue potential and cost to serve (including model inference and infrastructure costs).
- Ensure AI products are designed to be commercially viable and sellable from day one, with clear differentiation and a compelling, evidence-based return on investment for clients.
- Own the go-to-market plan in partnership with Sales, Marketing and Client Success, including launch planning, positioning, messaging and pricing.
- Track commercial performance after launch (for example pipeline, revenue, client adoption, retention and margin) and use it to guide roadmap decisions.
- Product Delivery & Launch
- Own AI products end to end, driving development from discovery and prototype through MVP, pilot and full production launch, and making sure products reach market on time and to the expected standard.
- Remove blockers and make clear trade-off decisions on scope, quality, cost and time, keeping teams focused on a successful launch rather than proofs of concept that stall.
- Work closely with AI Research Engineers, Data Engineers and Software Engineers to design and deliver AI models, algorithms and solutions that meet client needs.
- Translate use cases into clear product requirements, user stories and acceptance criteria, including model performance, quality and data requirements.
- Champion Agile product development, ensuring timely delivery of high-quality products through iterative releases.
- Apply practical, hands-on knowledge of building Generative AI products, including model selection, prompt and context engineering, retrieval-augmented generation (RAG), agentic workflows, evaluation and guardrails, to guide build-versus-buy and solution design decisions.
- Collaborate with Design on intuitive, trustworthy user experiences for AI-driven features, including how outputs, confidence and sources are presented to users.
- Performance, Quality & Responsible AI
- Define success metrics for AI products, covering both business outcomes and model quality (for example accuracy, reliability, latency, cost and user adoption), and track them post-launch.
- Establish evaluation, monitoring and feedback processes so that models are validated against business objectives and continuously improved.
- Work with Data Protection and legal teams to ensure AI products align with regulatory and ethical expectations, including data privacy, transparency, bias and human oversight.
- Identify and manage product risks, including model limitations, data quality and third-party model dependencies.
- Enablement & Collaboration
- Communicate AI capabilities, limitations and progress clearly to technical and non-technical stakeholders at all levels.
- Support Sales, Client Success and Product Consultants with product positioning, demonstrations, objection handling and training materials, so they can sell ZILO’s AI products with confidence.
- Stay current with advances in AI, machine learning and data science, and assess new technologies for fit with ZILO’s products.
Essential
- Proven experience in product management (typically 5+ years), with a track record of taking products from concept through to market launch and commercial success, ideally in fintech, Saa S, financial services or regulated environments.
- Demonstrable, real-world experience of building and launching products where Generative AI is at the core, not simply an added feature, including products live in production and used by paying clients, ideally in a regulated environment.
- Hands-on knowledge of the Generative AI product lifecycle, including LLM selection, prompt design, retrieval-augmented generation, evaluation, guardrails, and managing cost, latency and reliability at scale.
- Strong commercial acumen, with experience of building business cases, and working with Sales and Marketing to bring products to market.
- Strong understanding of AI technologies, frameworks and best practice, including machine learning concepts, LLMs and Generative AI, and how models are trained, evaluated and deployed.
- Ability to work credibly with AI research engineers and translate complex technical concepts into actionable product strategy.
- Proficiency in data analysis tools and techniques, with a solid understanding of data science principles.
- Experience with Agile product development methodologies and tools such as JIRA and Confluence.
- Knowledge of user experience best practice and design thinking principles.
- Excellent analytical and problem-solving skills, with a data-driven approach to decision-making.
- Exceptional communication and interpersonal skills, with the ability to engage and influence stakeholders at all levels.
Desirable
- Experience with agentic AI, multi-model architectures or fine-tuning small language models for specialist domains.
- Understanding of AI governance and regulation (for example the EU AI Act and GDPR) and of responsible AI practices.
- Familiarity with cloud platforms (AWS, Azure or GCP) and MLOps concepts.
- A passion for emerging technologies and a commitment to continuous learning.
- Success Measures
- A clear AI product strategy and prioritised roadmap, aligned to client and business value.
- AI products taken from concept to market launch on schedule, delivered to agreed quality with defined and tracked model performance metrics.
- AI products that are commercially viable and sellable, evidenced by client contracts, revenue growth and healthy margins.
- Client and internal adoption of AI products, and evidence of measurable efficiency or insight gains.
- AI products that meet ZILO’s compliance, security and responsible AI standards
- Enhanced leave - 38 days inclusive of Public Holidays
- Private Health Care including family cover
- Life Assurance – 5x salary
- Flexible working-work from home and/or in our London Office
- Employee Assistance Program
- Pension Salary Sacrifice
- Holiday selling scheme
- Cycle to work and nursery salary sacrifice schemes
- EMI Share Option Scheme after a qualifying period
- #J-18808-Ljbffr
AI Product Manager in London employer: ZILO Technology, Ltd.
ZILO is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the rapidly evolving digital asset landscape. With a strong focus on employee growth, ZILO provides extensive training opportunities, enhanced leave, and a unique 'work from anywhere' policy, making it an attractive choice for professionals looking to make a significant impact in the financial services sector across Europe.
StudySmarter Expert Advice🤫
We think this is how you could land AI Product Manager in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at ZILO Technology, Ltd. or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to ZILO Technology, Ltd..
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like ZILO Technology, Ltd..
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like ZILO Technology, Ltd. that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace AI Product Manager in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at ZILO Technology, Ltd..
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at ZILO Technology, Ltd. and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at ZILO Technology, Ltd.
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If ZILO Technology, Ltd. uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.