Multiverse

4 weeks ago

Principal AI Engineer, Edinburgh

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Lead architectural decisions for AI agent systems, ship production AI agents, set engineering standards, and drive the technical strategy across multiple teams while collaborating with UK-based Scotland hub to modernise Multiverse’s AI-native platform.

Location: Edinburgh

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Sr. Manager level

Key Responsibilities

•Own the AI agent architecture. Design the orchestration layer, memory and context management, evaluation framework, and integration APIs that all agent products build on.
•Ship production agents. Write and review code and own what goes to production; deliver at least one major agent system in the first six months.
•Set the engineering standard. Define how Multiverse builds with AI — evaluation methodology, multi-agent coordination patterns, tool design, guardrails, and observability.
•Build the integration layer. Create the APIs, MCPs, and shared data contracts connecting agents to the platform, content systems, and internal tools with London teams.
•Drive technical strategy. Translate product and business goals into a coherent AI engineering roadmap and socialise it with leadership and the exec team.

Pay and Benefits

Perks:Health InsuranceGym MembershipRemote WorkLearning BudgetWellness Stipend

Key Requirements

•Shipped multi-agent systems to real users with strong understanding of context management, model selection and routing, token economics, caching, prompt optimisation, tool use and failure handling.
•Experience defining engineering standards adopted across an organisation, including evaluation methodologies, multi-agent coordination patterns, tool design, guardrails, and observability.
•Full-stack delivery experience across LLM integration, backend services, data pipelines, and frontend, with hands-on coding and production ownership.
•Ability to translate product and business goals into a coherent AI engineering roadmap and socialise it with engineering leadership and exec teams.
•Background as a founding engineer or technical co-founder is a plus.

Skills:CommunicationProblem-solvingLeadershipCross-functional collaboration

Languages:English

Tech Stack:Claude CodeLLMAPIsData pipelinesBackendFrontendPythonDockerKubernetes

Company Brief

Multiverse

Multiverse provides apprenticeship and upskilling programs combining human coaching with AI to train employees in data, tech and AI skills, partnering with large organisations to deliver on-the-job learning and career mobility.

Industry: Corporate Training

Company Size: Enterprise (1,001+ employees)

Revenue: USD 50M to 100M

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series D

Headquarters: London, United Kingdom

Founded: 2016

Glassdoor: 2.9

Website LinkedIn Glassdoor

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Multiverse

4 weeks ago

Principal AI Engineer, Edinburgh

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Location: Edinburgh

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Sr. Manager level

Key Responsibilities

•Own the AI agent architecture. Design the orchestration layer, memory and context management, evaluation framework, and integration APIs that all agent products build on.
•Ship production agents. Write and review code and own what goes to production; deliver at least one major agent system in the first six months.
•Set the engineering standard. Define how Multiverse builds with AI — evaluation methodology, multi-agent coordination patterns, tool design, guardrails, and observability.
•Build the integration layer. Create the APIs, MCPs, and shared data contracts connecting agents to the platform, content systems, and internal tools with London teams.
•Drive technical strategy. Translate product and business goals into a coherent AI engineering roadmap and socialise it with leadership and the exec team.

Pay and Benefits

Perks:Health InsuranceGym MembershipRemote WorkLearning BudgetWellness Stipend

Key Requirements

•Shipped multi-agent systems to real users with strong understanding of context management, model selection and routing, token economics, caching, prompt optimisation, tool use and failure handling.
•Experience defining engineering standards adopted across an organisation, including evaluation methodologies, multi-agent coordination patterns, tool design, guardrails, and observability.
•Full-stack delivery experience across LLM integration, backend services, data pipelines, and frontend, with hands-on coding and production ownership.
•Ability to translate product and business goals into a coherent AI engineering roadmap and socialise it with engineering leadership and exec teams.
•Background as a founding engineer or technical co-founder is a plus.

Skills:CommunicationProblem-solvingLeadershipCross-functional collaboration

Languages:English

Tech Stack:Claude CodeLLMAPIsData pipelinesBackendFrontendPythonDockerKubernetes

Company Brief

Multiverse

Industry: Corporate Training

Company Size: Enterprise (1,001+ employees)

Revenue: USD 50M to 100M

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series D

Headquarters: London, United Kingdom

Founded: 2016

Glassdoor: 2.9

Website LinkedIn Glassdoor