Software Engineer III

Description -Turn ambitious ideas about the future of learning into working evidence fast. Join Pearson Labs to prototype with AI and emerging technology test what matters with real users and help shape where Pearson invests next. Also known in the market as: Innovation Engineer; Prototyping Engineer; Applied AI Engineer; R&D Software Engineer.

Pearson Labs is the applied R&D function within the Office of the CTO. Our job is to explore experiment with and prototype emerging technologies that could transform how the world learns is assessed and works. Under Pearsons newly approved Innovation Architecture Labs is part of a shared innovation capacity that business units across the company draw on to get new concepts moving fast with rapid prototyping early-stage technical support and evidence that helps leaders make confident continue pivot or stop decisions.

This is real work with real the last year the team has run an eight-week beta with university physics educators filed patents from prototype work placed in company hackathons and built everything from AI tutors and interactive learning objects to haptic hardware for skills training smart-glasses learning experiences room-scale immersive environments multi-agent assessment systems knowledge graphs and voice agents demoing that work to executives and customers around the world. The lab itself operates as a working customer surface: sales teams product teams and customers come through the space and what we build gets used in front of them. We are customer-centric technology-first systems-focused and relentlessly curious about whats next.

Most software roles are defined by a specialism. This one is defined by a contribution: taking an idea about the future of learning and turning it into working evidence fast. Jobs across product and engineering are reshaping in the age of AI and we think the interesting roles now organise around what you move forward rather than which discipline you sit Labs that contribution is the prototypers: discovering whats possible building the version that proves it and handing it over well.

As an Innovation Engineer you will work across the Labs portfolio building prototypes and running experiments with emerging technologies. Some weeks that means a scrappy proof of concept to answer a single question; other weeks it means carrying a validated prototype toward pilot quality with real users. You will help us answer big questions such as:

• What will the future of learning look like
• How can we create meaningful experiences for learners and educators through new technology
• Which technologies will make the biggest impact in learning assessment and work over the next decade

You will get unusual visibility for an engineering role: your prototypes will be seen and used by senior leaders business units and customers and your evidence will directly shape where Pearson invests next.

• Design build and ship prototypes that test hypotheses about learning assessment and work from quick demos to multi-technology systems piloted with real users.
• Run experiments properly: framed around a validated story user-first with measurable objectives and honest findings whether the answer is yes or no.
• Work hands-on with emerging technologies currently including AI agents multimodal models immersive and spatial computing and knowledge graphs and help the team understand what they mean for learning.
• Get to a minimal viable system quickly keep it simple and add complexity only when the evidence earns it.
• Tell the story of the work: demos showcases short technical notes and contributions to our public portfolio site.
• Treat innovation as a team sport. You will build alongside our Learning Science teams who ground prototypes in how people actually learn with the other innovation teams around the business including AI research Ventures and the innovation teams inside each business unit with product teams who take our work forward and with the business units who bring us their hardest problems.
• Document and hand over cleanly so validated work can move into product engineering without losing what made it work.

We are an AI-native team. We build with coding agents and agentic workflows daily and we treat AI as leverage that lets a small team cover ground that used to need a much larger one. Our stack is pragmatic and moves fast: Claude Code and Cursor Railway internal hosting platforms developed by our colleagues and dedicated to rapid prototyping use cases and cloud deployment patterns designed for speed. None of it is precious; the right tool is the one that gets to evidence fastest.

Our method draws on innovation engineering practice: start with a story worth validating put the user before the system architecture work from the resources in front of you break systems into simple parts reduce the downside rather than optimise the upside and measure progress with objectives you can actually check. Every programme runs on a hypothesis and closes with an explicit scale pivot or stop decision and we record the stops as proudly as the wins because a weak proposition stopped in time frees capacity for a strong one. Labs owns the earliest stages of Pearsons innovation funnel from sensemaking through proof of concept with a defined graduation into product development so prototypes here are judged on the decisions they enable.

Were looking for entrepreneurial technologists who are excited to tackle ambiguous problems with ingenuity and energy. You should have:

• Technical excellence: strong programming and prototyping skills with working fluency in modern software design APIs and cloud deployment. You can take an idea to a working system on your own.
• AI fluency: genuine hands-on experience building with AI whether thats LLM-powered applications agents or AI-assisted development workflows and an appetite to keep pace as the field moves.
• Creative problem-solving: you generate original approaches to loosely defined problems and know when to test several cheaply rather than commit to one.
• Customer focus: a desire to understand the problems learners and educators actually face and to let their feedback beat your assumptions.
• Systems thinking: a knack for seeing how technologies products and ecosystems interconnect.
• Rigour: disciplined tracking documentation and communication of the innovation process. Fast does not mean sloppy.
• Curiosity and passion for learning: you tinker you read you build things nobody asked for and education is a domain you actually care about.

We are open to a range of experience levels and we will shape the level of the role around the person. As a guide:

• Earlier in your career youll own well-scoped experiments end to end: building functional prototypes running usability tests and presenting findings to the team and stakeholders.
• With more experience youll lead multi-technology prototypes at higher maturity drive experiments from hypothesis through validated outcome mentor other engineers and influence which ideas the lab pursues.
• At the most senior level youll act as a technical advisor across the portfolio: setting engineering standards for applied research carrying prototypes toward production readiness with product teams and generating invention disclosures and patents from the work.

If youre unsure whether youre senior enough apply anyway. We care more about what youve built and how you think than about years served.

• Experience communicating complex technical ideas to broad audiences through demos presentations writing or social media.
• Familiarity with design thinking rapid prototyping or lean startup methodologies.
• Interest in learning science neuroscience or human-computer interaction.
• A network of technologists designers and builders especially in EdTech.
• Patents publications hackathon wins or a portfolio of side projects.

• Youre a hands-on maker who loves to prototype and tinker with new tools.
• You thrive in ambiguity and adapt quickly as priorities shift with the evidence.
• Youre as comfortable deep in code as you are demoing your work to customers and senior leaders.