Senior Learning Programme Designer
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Multiverse is the upskilling platform for AI and Tech adoption.
We have partnered with 1,500+ companies to deliver a new kind of learning that's transforming today’s workforce.
Our upskilling apprenticeships are designed for people of any age and career stage to build critical AI, data, and tech skills. Our learners have driven $2bn+ ROI for their employers, using the skills they’ve learned to improve productivity and measurable performance.
In June 2022, we announced a $220 million Series D funding round co-led by StepStone Group, Lightspeed Venture Partners and General Catalyst. With a post-money valuation of $1.7bn, the round makes us the UK’s first EdTech unicorn.
But we aren’t stopping there. With a strong operational footprint and 800+ employees, we have ambitious plans to continue scaling. We’re building a world where tech skills unlock people’s potential and output.
Join Multiverse and power our mission to equip the workforce to win in the AI era.
Overview:
The Senior Learning Programme Designer owns the design process for curricula and learning experiences at Multiverse. This role is AI-first, with AI tools being utilised to design and develop high-level curricula and individual learning assets that meet both our internal design standards as well as meeting external regulatory requirements. The Senior Learning Programme Designer will collaborate closely with product owners, asset designers, instructional designers and contractors to develop materials to support both synchronous and asynchronous learning, ranging from two year apprenticeships in AI Product Engineering to training for short burst skills training for first time managers. They should be fascinated by the potential for AI to make learning personalised, whilst recognising the need for close attention to quality as AI learning scales. At the heart of their quality assurance is the impact that the learning will have on both individual learners and the businesses who support them to take up these opportunities.
What you’ll do:
- Lead the creation of curricula and frameworks for our the AI production engine, ensuring alignment with the Multiverse MAGE (measured, applied, guided and equitable) framework and compliance with regulatory standrds.
- Manage the development lifecycle for programme assets. Create and manage timelines and budgets for producing programme learning materials, taking into account the interaction between AI and human centred processes. Onboard, direct and manage the day-to-day work of contractors and/or subject matter experts if required.
- Quality assure learning materials. Serve as the final validator of content produced by the AI machine and that which is human generated, ensuring quality, accuracy, and adherence to design principles and a cohesive and impactful learning experience.
- Utilise learner and client data to inform AI machine improvements. Utilise insights from key data sets to optimise the AI agents to make effective customisation and design decisions, and make recommendations for new product features to the wider product team.
- Champion AI adoption and best practices. Lead the communication of the AI machine's capabilities to other teams and stakeholders, building buy-in and defining how the new content will be delivered andused.
- Influence and manage cross-functional teams. Apply advanced communication strategies to build consensus and secure buy-in from product, engineering, and delivery teams to ensure the end-to-end learning product is harmonised with the AI-driven approach.
What you’ll bring:
- Curriculum Design Expertise: Significant experience applying backward design principles to create measurable learning outcomes and aligned assessments for learning and skills development programmes.
- AI & Technical Literacy: A solid knowledge of generative AI and workflow automation tools. The ability to translate pedagogical rules into a technical rule set that can be executed by an AI machine. Solid understanding and application of prompt engineering principles for effective interaction with AI models.
Nice to have:
- Additional experience designing for technical disciplines such as Data, Leadership, Software Engineering
- AI.Bachelor's or Master's degree in a related field, such as instructional design, education, or organisational development
Benefits
- Time off - 27 days holiday, plus 5 additional days off: 1 life event day, 2 volunteer days, 2 company-wide wellbeing days (M-Powered Weekend) and 8 bank holidaysper year
- Health & Wellness- private medical Insurance with Bupa, a medical cashback scheme, life insurance, gym membership & wellness resources through Wellhub and access to Spill - all in one mental healthsupport
- Hybrid work offering - for most roles we collaborate in the office three days per week with the exception of Coaches and Instructors who collaborate in the office once a month
- Work-from-anywhere scheme - you'll have the opportunity to work from anywhere, up to 10 days per year
- Space to connect: Beyond the desk, we make time for weekly catch-ups, seasonal celebrations, and have a kitchen that’s always stocked!
Our Commitment to Diversity, Equity and Inclusion
We’re an equal opportunities employer. And proud of it. Every applicant and employee is afforded the same opportunities regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. This will never change. Read our Equality, Diversity & Inclusion policy here.
Our Commitment to Safeguarding
Multiverse is committed to safeguarding and promoting the welfare of our learners.
We expect all employees to share this commitment and adhere to our Safeguarding Policy, our Prevent Policy and all other Multiverse company policies. Successful applicants will be required to undertake at least a Basic check via the Disclosure Barring Service (DBS).
For roles that will involve a Regulated Activity, successful applicants must also undergo an Enhanced DBS check, including a Children’s Barred List check and a Prohibition Order check. Roles involving Regulated Activity may interact with vulnerable groups, therefore are exempt from the Rehabilitation of Offenders Act 1974 meaning applicants are required to declare any convictions, cautions, reprimands, and finalwarnings.
Providing false information is an offence and could result in the application being rejected or summary dismissal if the applicant has been selected, and possible referral to the police and the DBS.