Role: AIOps Technical Delivery LeadLocation: Barcelona, SpainMode: Hybrid (2 days onsite)Type: ContractJob Description:AIOps Technical Delivery LeadCompany DescriptionWe are seeking a talented and analytical Data Scientist to join our team. As a Data Scientist, you will play a crucial role in leveraging data to uncover valuable insights, drive data-driven decision-making, and support our organization's goals.Job DescriptionThe AI Engineering team is looking for a hands-on senior technical leader to define, build, and scale our initial AIOps capability for AI and ML systems in production.Reporting into the AI Engineering Lead and aligned with the Group Head of AI Technology, you will play a pivotal role in ensuring AI-enabled services are reliable, observable, cost-effective, and operable at enterprise scale.This is a player–coach role. You will personally drive the technical vision, scope, and roadmap for AIOps, while leading and mentoring a small, high-impact team of 1–2 engineers as the capability ramps up. You’ll move fast to deliver early value, while laying the foundations for a scalable, enterprise-grade approach.What you’ll focus onYou will own the runtime lifecycle of AI systems, including:Observability, monitoring, and alertingIncident prevention, response, and automated remediationModel, data, and performance drift detectionRuntime performance optimisation and operational cost controlOperating in a complex, multi-tenant environment across multiple Operating Companies, you will reduce operational complexity by defining clear patterns, tooling, and ways of working that increase confidence in AI systems and reduce toil.Working with product teamsA core part of the role is partnering closely with Product Teams to embed MLOps and operational capabilities into AI services from the outset. You will:Ensure operational requirements are considered early in the product lifecycleEnable consistent adoption of enterprise-grade practices across squadsHelp product teams deliver AI solutions faster, more reliably, and at lower operational risk technical leadership & influenceYou will act as the technical authority for AIOps, guiding multiple squads toward consistent, data-driven operational practices. You will:Maintain an “always-on” view of the AIOps and MLOps landscape, including emerging GenAI operational use casesAssess new tools, platforms, and approaches, modelling their cost, benefit, and riskWork closely with the AI Engineering Lead and Tech Leads AI Labs (London & Barcelona) to build a strong, aligned engineering communityDrive measurable improvements in reliability, efficiency, and ROI for AI investments across the Group Key responsibilitiesBe deeply hands-on in the design, build, and rollout of AIOps capabilities, especially during initial ramp-upDefine and deliver the first production-ready AIOps solutions, including observability, anomaly detection, and automationLead, mentor, and prioritise work for a small AIOps team (1–2 engineers)Shape and own the technical vision, scope, and roadmap for AIOps within IMSRapidly prototype and productionise solutions to demonstrate value and build momentumEstablish standards, patterns, and guardrails for operating AI/ML systems in productionDesign and implement model, data, and performance drift detection approachesApply a structured, data-driven approach to identifying and reducing operational and technical riskModel and optimise the runtime and operational costs of AI-enabled servicesOwn and contribute to technical governance, including the IMS KDD (Key Design Decision) processCollaborate closely with cloud, data platform, security, SRE, and operations teamsIdentify and sponsor improvements to operational processes, tooling, and ways of workingAssess third-party AIOps, observability, and automation tools for enterprise readiness and cost-effectivenessBuild architectural consensus with product, cloud, data science, and data platform teamsQualifications, Experience, Qualities10+ years of experience working in enterprise engineering environments, with a proven track record of delivering and operating complex production systemsDemonstrated ability to provide hands-on technical leadership, including writing code, integrating tooling, andleading delivery across multiple squadsStrong experience operating AI/ML systems in production, including monitoring, incident management, and lifecycle managementSolid understanding of MLOps, CI/CD pipelines, and routes to live for data science and ML workloadsExperience with observability platforms, alerting systems, automation, and reliability engineering practicesProven experience bootstrapping new technical capabilities and scaling them in complex organisationsAbility to balance rapid delivery with operational stability, risk management, and long-term sustainabilityOutstanding communication and interpersonal skills, with the ability to influence engineers, stakeholders, and senior leadersAbility to frame complex technical and operational considerations for time-poor executives to support decision-makingWillingness and ability to be on-site in Barcelona and travel to London where requiredEnthusiastic, pragmatic, forward-looking, and comfortable operating in ambiguityAirline industry experience is preferred