AI Staff Engineer

Multiverse is the upskilling platform for AI and Tech adoption.

We have partnered with 1500 companies to deliver a new kind of learning thats transforming todays 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 theyve 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 UKs first EdTech unicorn.

But we arent stopping there. With a strong operational footprint and 800 employees we have ambitious plans to continue scaling. Were building a world where tech skills unlock peoples potential and output.

Join Multiverse and power our mission to equip the workforce to win in the AI era.

At Multiverse we believe technology should empower everyone to achieve their potential. As an AI Solutions Engineer on our Learning team youll transform cutting-edge AI research into real-world tools that make Multiverses learning content smarter more personalised and truly impactful for thousands of users. Join us to architect and lead the development of tooling that enables our Learning team to create world class experience building upon the AI tooling weve developed over the last year and evolve it to new capabilities and potential.

Key Responsibilities

• Design Architect & Deliver AI Solutions: Partner with Product Design and Data teams to shape and deliver AI-powered features that generate real impact to our learners value for our customers and align with Multiverses mission.

• Establish LLM Best Practices: Define the technical standards and governance for leveraging Large Language Models (LLMs) including design fine-tuning and integration for high-impact production use cases such as content generation semantic search summarisation and personalised learning experiences.

• Build & Integrate Models: Develop fine-tune and embed machine learning models into production systems using tools like Cursor and Gemini ensuring they are fast scalable and dependable.

• Own the End-to-End Lifecycle: Take responsibility for the journey from raw data through experimentation deployment to users and continuous iteration.

• Measure What Matters: Track the performance accuracy and adoption of AI features and use those insights to drive constant improvement.

• Mentor and Scale Expertise: Mentor and coach engineers across teams sharing your deep expertise to make AI approachable and set the direction for best practices significantly elevating the teams capabilities.

• Lead in MLOps & Cloud Infrastructure: Build robust pipelines for deployment and monitoring using AWS cloud services and modern MLOps best practices.

• Champion Innovation: Keep us ahead of the curve by exploring new AI tools including Cursor and Gemini and applying them to create exceptional user experiences.

• Drive Organisational Adoption: Champion new technologies and approaches (including AI-assisted tools) driving their successful adoption across multiple teams while balancing experimentation with pragmatic delivery.

• Cross-Team Influence: Act as a key technical advisor and connector across product design and engineering ensuring alignment on strategic initiatives.

About you

• Proven Staff-Level experience: 6-7 years in software engineering with strong understanding of Applied AI fundamentals Experience working in cross-functional product teams

• LLM Expertise: Experienced in working with large language models (e.g. GPT Claude Gemini Pro) for production use cases including prompt engineering evaluation and safety & inclusivity considerations.

• Strong Engineering Skills: Proficient in Python and TypeScript with experience building APIs microservices and cloud-native applications.

• Experience with AI Tools: Familiarity with emerging AI tooling platforms such as Cursor and Gemini is highly desirable.

• Cloud & MLOps: Practical experience deploying AI solutions on AWS with a strong grasp of version control observability and evaluation pipelines.

• Data Skills: Skilled at working with structured and unstructured data applying preprocessing and feature engineering techniques.

• User Focus: You can translate complex AI capabilities into product experiences that feel effortless and intuitive.

• Collaborative Approach: You work best in creative and cross-functional teams and thrive when building together.

Growth Mindset: Youre curious open to feedback and excited to share what you learn while contributing to an inclusive high-performing culture.

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 holidays per 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 health support

• 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 - youll 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 thats always stocked!

Our Commitment to Diversity Equity and Inclusion

Were 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 Childrens 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 final warnings.

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.

Required Experience:

Staff IC