At a Glance
- Tasks: Create innovative AI products and prototypes while collaborating with diverse teams.
- Company: Join a forward-thinking online university revolutionising education.
- Benefits: Flexible working hours, remote work, and opportunities for continuous learning.
- Other info: Dynamic role with a focus on experimentation and real-world impact.
- Why this job: Be at the forefront of AI innovation and shape the future of education.
- Qualifications: 2-4 years in product development with strong AI experience and coding skills.
The predicted salary is between 70000 - 90000 £ per year.
- Position Title: AI Product Specialist
- Working
Rhythm: Innovation is a 24/7 pursuit, but we value your downtime.
While our typical working hours are 9am-5pm in your timezone, we embrace flexibility and trust you to manage your schedule to meet your individual needs and peak productivity times.
Occasionally, longer hours may be to tackle challenges, support new releases, or contribute to time-sensitive initiatives.
- Reporting To: Chief Product Officer
- Role
We're looking for someone who lives at the edge of AI possibilities—someone who wakes up thinking about what they can build with the latest models, tools, and techniques.
You're the kind of person who has strong opinions about Claude vs Chat GPT vs Gemini because you've actually shipped things with all of them.
You experiment relentlessly, you vibe code like others scroll social media, and you want to build the future.
As our AI Product Specialist, you'll be our internal R&D lab and strategic advisor rolled into one.
You'll prototype agentic experiences, pressure-test new AI capabilities, and help me make smart bets on what we should build.
You'll balance hands-on building with strategic thinking—shipping experiments fast while developing frameworks for how we should think about AI across our product.
At Nexford we're building a new kind of university: one that's affordable, flexible, relevant, and 100% online.
One that prepares learners for the careers of tomorrow, without the burden of student debt.
Key Responsibilities
- Ship rapid AI experiments: Build working prototypes of agentic workflows, conversational interfaces, and AI-assisted features.
Move from idea to clickable demo in days, not weeks.
You're comfortable with imperfect MVPs that teach us something and can help get buy in for deeper investment.
- Develop strategic recommendations: Translate hands-on learning into actionable guidance for the CPO. Where should we invest our AI resources in?
- Stay bleeding-edge current: The AI space is rapidly changing, with new models and techniques regularly emerging.
You'll stay on top of the latest and encourage us to integrate new concepts.
- Design agentic experiences: Go beyond chatbots and build fully agentic systems with orchestration.
- Bridge technical and product thinking: Translate between what's technically possible and what creates real user value.
- Cross-functional
Collaboration: Collaborate with cross-functional teams across Nexford, including Learner Success, Academic Operations, Technology, and Marketing, to ensure a cohesive and seamless learner experience.
Additionally, foster successful market introduction of new products, features, and experiences.
- Data-Driven
- Decision
Making: Utilize user research, data analytics, and learner feedback to assess product performance, identify areas for improvement, and inform future iterations.
- Continuous Improvement: Promote a culture of continuous improvement, iterating on products and services based on feedback and data insights.
Skills & Qualifications
- 2-4 years working to ship features and products, with meaningful AI experience: You've built real features that real users have used.
Bonus if you've worked on conversational AI, agents, or developer tools.
- Vibe coding as a superpower: You can go from idea to working code fast.
You're comfortable with Claude/Cursor/Copilot/Lovable/v0 and whatever comes next.
You write code to think, not just to ship.
You know when to polish and when to stay scrappy.
- Deep curiosity about AI tools and techniques: You have strong opinions (weakly held) about RAG architectures, prompt engineering, function calling, fine-tuning, and when to use what.
- Tinkerer mentality: You build side projects. You have a personal AI stack. You like to experiment.
- Product taste alongside technical chops: You know the difference between a cool demo and a useful feature.
- Clear communication: You can explain complex AI concepts to non-technical stakeholders to get buy-in and build a shared understanding.
If you're passionate about transforming lives through education and have a proven track record of delivering exceptional customer experiences, we encourage you to apply!
StudySmarter Expert Advice🤫
We think this is how you could land Remote AI Product Specialist in Bury
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We think you need these skills to ace Remote AI Product Specialist in Bury
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Grabjobs, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Grabjobs. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Grabjobs
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
