Lead Applied AI Engineer

loveholidays

. Lead and line-manage Applied AI engineers, setting goals, providing feedback and coaching, supporting career development, managing performance, and assisting recruitment and onboarding .

Posted 10/28/2026full-timeLondon • United KingdomSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading Applied AI engineering teams, managing supplier relationships, and delivering AI workflows while ensuring operational performance and compliance with governance standards. Proficient in making architecture decisions and optimizing cloud-based services for business outcomes.

Highest-signal resume keywords

Line Management Of EngineersApplied AI Workflows DeliveryThird-Party Supplier ManagementCloud-Based Business Systems AdministrationArchitecture Decision-Making

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Applied AI WorkflowsREST API DesignCloud Environments ManagementCI/CD PracticesGoogle Cloud PlatformOrchestrationIncident ManagementSecure Operational PracticesEvaluation Criteria EstablishmentTool-Using Agents Standards

Soft Skills

Coaching And DevelopmentCollaborative Team BuildingCommercial JudgementStakeholder InfluencePerformance Management

Tools & Technologies

Google ADKSaaS PlatformsAutomation PipelinesObservability ToolsIntegration Frameworks

Industry Keywords

Service HealthChange ManagementDocumentation StandardsGovernanceLicensing And Renewals

Tech Stack

Tools & technologies

CloudGoogle Cloud Platform

About the role

Key responsibilities & impact

Lead and line-manage Applied AI engineers, setting goals, providing feedback and coaching, supporting career development, managing performance, and assisting recruitment and onboarding
Set technical direction and delivery roadmap with business and technology stakeholders
Prioritise work, allocate capacity and manage dependencies to deliver measurable business outcomes
Provide hands-on technical leadership for applied and agentic AI workflows, integrations and automation pipelines
Guide architecture, review designs and code, and contribute to complex or high-impact engineering work
Set standards for building, testing and evaluating tool-using agents with Google ADK or similar frameworks
Ensure safe tool access, human oversight and production readiness
Own operational performance across AI-enabled services and SaaS platforms, including service health, access, releases, usage and cost
Lead incident escalation and continuous improvement with clear evaluation criteria and service measures
Own account management for third-party SaaS suppliers and run service and roadmap reviews
Hold suppliers accountable for service levels, resolve escalations and coordinate delivery with internal priorities
Manage supplier and contract lifecycle with procurement, finance, legal and security
Manage SaaS and AI services spend, forecast costs, explain variances, optimise licences and consumption, and inform build-versus-buy decisions
Establish standards for secure change management, documentation, runbooks and governance
Communicate progress, risks and trade-offs and ensure clear service ownership and support arrangements

Requirements

What you’ll need

Experience line-managing engineers, coaching and developing people, managing performance and leading delivery
Ability to set direction, prioritise competing demands and build a collaborative, accountable team
Experience owning third-party supplier relationships, service reviews, escalations, licensing and renewals
Commercial judgement and ability to work with procurement, finance, legal and security
Experience leading administration and lifecycle management of cloud-based business systems, including configuration, user access, environments, integrations and releases
Strong experience delivering applied and agentic AI workflows combining models, tools and business data
Experience with orchestration, retrieval-augmented generation and evaluation
Ability to make architecture and build-versus-buy decisions, establish engineering standards and guide others
Familiarity with Google ADK or similar frameworks is desirable
Strong hands-on engineering skills
Experience designing and reviewing REST API, webhook, event-driven or scheduled integrations
Experience operating production services in cloud environments, preferably Google Cloud Platform
Experience using CI/CD, observability, incident management and secure operational practices
Ability to explain technical and commercial trade-offs, influence stakeholders and connect delivery to business outcomes

Benefits

Comp & perks

Company pension contributions at 5%
Individualised training budget for you to learn on the job and level yourself up
Discounted holidays for you, your family and friends
25 days of holidays per annum plus 8 public holidays, increasing by 1 day for every second year of service up to a maximum 30 days per annum
Ability to buy and sell annual leave
Cycle to work scheme
Season ticket loan
Eye care vouchers
Inclusive and accessible hiring process with interview adjustments available