Senior Product Engineer | Full-Stack & AI

Build AI products customers use. Own the decisions that make them work.

MBN Solutions is partnering with an early-stage AI business to hire a Senior Product Engineer who wants a direct hand in shaping the product.

You’ll work closely with the founders and customers, taking meaningful problems from first conversation through to production. You’ll help decide what to build, work across the stack and see how your decisions perform in customers’ hands.

We’re looking for someone who combines strong software engineering with product judgement: an engineer who asks good questions, makes thoughtful technical decisions and takes responsibility for the outcome after release.

The opportunity

This is a role for someone who enjoys turning ambiguity into a useful product.

You might start by exploring a customer’s workflow, identify where AI can make a meaningful difference, then build the interface, backend services and data integrations needed to deliver it. You’ll define how to evaluate the result, ship incrementally and improve it using customer feedback.

You’ll have meaningful ownership of both what gets built and how it works. That means room to influence the product, alongside the responsibility to make it reliable, understandable and useful.

What you’ll own

• Products from discovery to delivery. Understand the customer problem, shape the approach and build complete experiences across the frontend, backend and data layer.
• AI-powered workflows. Bring models, tools, data and human review together, with sound judgement about where AI adds value and where conventional software is the better choice.
• Evaluation and reliability. Define what good looks like, test against realistic cases and build validation, recovery and fallbacks into the experience.
• Data integrity. Understand where data comes from, how it changes and what it can support. Make outputs traceable and communicate uncertainty clearly.
• Production quality. Build maintainable software with appropriate testing, monitoring, security and failure handling, balancing quality, speed and cost.
• Continuous improvement. Deliver in achievable milestones, communicate trade-offs early and use real customer behaviour to guide what happens next.

What you’ll bring

You’re confident building with TypeScript and React, supported by backend experience in Python or Node.js. You can design APIs, integrate external services, manage background jobs and build responsive, intuitive interfaces.

You have strong SQL skills and experience with relational databases such as PostgreSQL, including schema design, data transformations and investigating data-quality issues.

AI features shipped to real customers

You’ve delivered and maintained LLM-powered product features in production. You understand prompt design, structured outputs, tool calling and multi-step workflows, including state management, failure recovery and human review.

You can explain how you evaluated those features, where they failed and what you changed to make them more dependable.

The judgement to own the outcome

You can take a loosely defined problem, identify what’s missing and turn it into a practical plan. You know when to move independently, when to seek input and when a change in scope needs a conversation.

You use AI confidently in your work and can explain, validate and take responsibility for what you ship.

You’re comfortable with Git, automated testing, CI/CD, Docker and cloud deployment. You can investigate production issues and implement appropriate logging, monitoring, authentication and access controls.

You’ll typically bring five or more years of professional engineering experience, although equivalent evidence of independently building and owning substantial production products is equally relevant.

Experience that would be particularly useful

You may have been a founder, founding engineer or early-stage product engineer. Experience with analytics products, data visualisation, recommendation systems or subscription businesses would also be valuable.

We’d welcome familiarity with experimentation and statistical reasoning, alongside practical experience using retrieval, embeddings or agent orchestration to solve customer problems.

Why this role?

• Work directly with founders and customers.
• Influence product direction and technical decisions.
• Own substantial product areas from discovery through to production.
• See the impact of your work and use that feedback to make it better.
• Build at the intersection of software engineering, AI and customer needs.

#J-18808-Ljbffr