At a Glance
- Tasks: Shape AI products that make a real difference for small businesses.
- Company: Fast-growing UK SME lender on a mission to provide fair finance.
- Benefits: Competitive salary, equity options, hybrid work culture, and growth opportunities.
- Other info: Diverse and inclusive team focused on innovation and collaboration.
- Why this job: Join us to define how AI transforms lending and operations.
- Qualifications: 3-6 years in product management or technical roles with strong programming skills.
The predicted salary is between 72000 - 88000 £ per year.
Lenkie is a fast-growing UK SME lender on a mission to give small businesses access to fair, fast, and flexible finance. We’re at an exciting inflection point — scaling our lending book and using AI across the business to power how we decide, operate and serve customers. This is a rare opportunity to shape how Lenkie adopts AI in production: working across the business to turn real operational problems into AI products that ship and make a measurable difference — and setting the template for how we use AI for years to come.
About the job
We are looking for a highly technical AI Product Manager who can operate at the intersection of product, engineering and business operations. You will embed with teams across Risk, Collections, Underwriting, Account Management and Operations to identify high-value problems, decide which opportunities are worth pursuing and build working AI prototypes yourself before partnering with Engineering to scale them into production. This is approximately a 60% product and 40% technical role. You will own product direction and prioritisation, but you must also be capable of building and evaluating credible AI applications independently. The ideal candidate will have a strong technical foundation, potentially as a software engineer, data scientist, technical founder or product engineer, and will have transitioned into a product-focused role within an AI-first or highly technical environment. At Lenkie, you will not simply write requirements and manage a backlog. You will be expected to understand workflows deeply, work directly with code, APIs and data, and prove that a solution works before significant engineering resources are committed.
Key Responsibilities
- AI Product Discovery: Embed with teams across Risk, Collections, Underwriting, Account Management and Operations to understand their workflows, diagnose problems and identify where AI can create meaningful value.
- Roadmap Ownership: Own and prioritise the AI product roadmap, ensuring every initiative is tied to measurable company objectives, customer outcomes or operational improvements.
- Hands-On Prototyping: Build working prototypes using LLMs, retrieval-augmented generation, agents, structured outputs, tool use and workflow automation.
- Technical Validation: Test the feasibility, quality, reliability, cost and operational value of potential solutions before committing significant engineering resources.
- Product Delivery: Work closely with Engineering to turn validated prototypes into secure, reliable and scalable production products.
- Data-Driven Decision Making: Use SQL and analytics to investigate problems, size opportunities, validate assumptions and measure the impact of products after launch.
- Adoption & Impact: Own adoption after deployment and ensure products become embedded within real workflows and produce measurable business outcomes.
- Cross-Functional Collaboration: Translate complex business problems into technical solutions and communicate AI capabilities, limitations and trade-offs clearly to technical and non-technical stakeholders.
Qualifications/Required Skills
- Experience: 3–6 years of experience across product management, software engineering, product engineering, forward-deployed engineering or a closely related role.
- Technical Foundation: You have previously worked in a hands-on technical role and are comfortable building software independently.
- Programming Ability: Strong proficiency in Python or TypeScript. You should be able to build an end-to-end prototype without relying entirely on an engineering team.
- Hands-On AI Experience: Practical experience building applications with LLMs, including prompting, structured outputs, tool calling, RAG, agents and evaluation.
- Evidence of Building: A track record of personally building and shipping working software products, AI applications, internal tools or production-quality prototypes.
- Technical Fluency: Strong understanding of APIs, webhooks, databases, authentication, asynchronous workflows and modern software architecture.
- Product Judgement: Strong ability to prioritise based on impact, define clear requirements, set success metrics and distinguish between genuine product opportunities and interesting technical experiments.
- Data Proficiency: Strong SQL and analytics skills, with the ability to investigate problems and measure impact independently.
- Commercial Thinking: Ability to connect technical work to revenue, customer experience, operational efficiency or risk reduction.
- Self-Starter Mentality: You thrive in an environment where not everything is defined. You investigate problems, build solutions and take ownership from discovery through deployment.
- Communication: Ability to explain technical concepts, AI outputs and model limitations clearly to non-technical stakeholders.
Nice to have
- Previous experience as a software engineer who transitioned into product management.
- Experience working within an AI-first company or a dedicated AI product team.
- Experience as a technical founder, product engineer, forward-deployed engineer or solutions engineer.
- Experience in fintech, lending, payments or another regulated industry.
- Experience building internal tools for underwriting, risk, operations, compliance or customer support.
- Experience with Anthropic Claude, OpenAI models or other foundation model platforms.
- Experience with AI observability, tracing and evaluation tools.
- Experience with workflow automation tools such as n8n, Temporal or similar platforms.
- Familiarity with AWS and cloud-based production environments.
How we reward performance
- Competitive Salary: Generous base salary plus meaningful equity options.
- Hybrid Culture: Three days per week in our London office to foster collaboration, with flexibility for the rest.
- Impact: The opportunity to define how a fast-growing lender adopts AI across its products and operations.
- Autonomy: Significant ownership over which problems we solve and how solutions are designed, validated and delivered.
- Technical Environment: Work closely with the CTO and a highly technical engineering team on complex financial and operational problems.
- Growth: A clear path towards senior product, AI product leadership or broader product and technology roles as the company scales.
We’re building a diverse, inclusive and supportive team where everyone can do their best work. We welcome applications from people of all backgrounds, experiences and perspectives, and we do not discriminate based on age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race, religion or belief, sex, or sexual orientation. If you require any reasonable adjustments during the recruitment process, please let us know.
AI Product Manager (Forward-Deployed) in London employer: Lenkie
Lenkie is an exceptional employer, offering a unique opportunity for an AI Product Manager to shape the future of AI in a fast-growing SME lender based in London. With a strong focus on employee growth, competitive salaries, and meaningful equity, Lenkie fosters a diverse and inclusive work culture where innovative ideas are encouraged and valued. Join us to make a real impact by helping small businesses access the finance they deserve while working in a hybrid environment that promotes collaboration and flexibility.
StudySmarter Expert Advice🤫
We think this is how you could land AI Product Manager (Forward-Deployed) in London
✨Join Product Management Meetups
Get involved in local product management meetups or workshops. These events are perfect for meeting industry folks, sharing ideas, and staying updated on trends. Plus, you never know who might be hiring—it's a fantastic way to make connections that could lead to a job at places like Lenkie!
✨Show Off Your Product Sense
Create case studies or mini-projects showcasing your product management skills, and share them on platforms like Medium or LinkedIn. This not only puts your skills on display but also boosts your visibility in the product community. Imagine how impressed the hiring team at Lenkie would be by your initiative!
✨Utilise Online Communities
Dive into online product management communities like Product Coalition or Mind the Product. Engage in discussions, ask questions, and share your insights. These platforms are goldmines for networking and finding hidden job opportunities—many companies often scout talent from within these circles.
✨Leverage Your University Network
If you’ve recently graduated or are still in uni, tap into your alumni network for connections in product management. Many universities have their own job boards and affinity resources to help graduates land roles. Don't forget to keep an eye out for job openings at Lenkie through your school's career services!
We think you need these skills to ace AI Product Manager (Forward-Deployed) in London
Some tips for your application 🫡
Show Off Your Product Passion:When applying for a product management role like AI Product Manager (Forward-Deployed), let your passion for developing products shine through in your cover letter. Share specific examples of products you've managed, how you solved user needs, and any successful outcomes you've achieved. This is your chance to showcase your understanding of the product lifecycle!
Highlight Your Cross-Functional Skills:Product management isn't just about understanding the product; it’s about collaborating with different teams! Make sure to emphasise your experience working with developers, designers, and marketers. Use your CV to showcase your ability to bridge gaps between these areas, and include relevant experiences that demonstrate your communication and leadership skills!
Include Your Metrics and Achievements:In a full-time product management application, data speaks volumes! Quantify your achievements wherever possible. Did you increase user retention by a certain percentage? Launch a product ahead of schedule? Include these metrics in your CV to paint a picture of your impact and effectiveness in previous roles.
Tailor Your CV to the Role:Make sure your CV is tailored for the AI Product Manager (Forward-Deployed) position at Lenkie. Use keywords from the job description and ensure your relevant experiences are front and centre. Highlight any certifications or relevant training you’ve completed that will make you stand out as a strong candidate for the role. And remember, we’re excited to see your application on our website!
How to prepare for a job interview at Lenkie
✨Understand the Product Life Cycle
As a product management candidate, we need to get our head around the complete product life cycle. Be prepared to discuss real-world examples of how you’ve managed product development from ideation to launch. Bring specific insights on tools like JIRA or Trello that can help streamline these processes.
✨Showcase Your Cross-Functional Skills
Product management is all about collaboration. We should be ready to highlight how we’ve worked across teams—think marketing, engineering, and design. Prepare to discuss scenarios where you had to mediate differing opinions and how you got everyone on board with a shared vision.
✨Prepare for Case Studies
In a full-time role, we can expect to encounter case study questions during our interviews. Practise solving hypothetical product problems on the spot, such as prioritising features for a new app or improving user engagement metrics. This will show our analytical thinking and decision-making skills.
✨Know Your Metrics
Let’s face it, numbers are our best friends in product management. We should prepare to discuss key performance indicators (KPIs) and how we've used analytics to inform product decisions. Dive into examples where data has driven our strategy for improvements or justified product changes.
