AIOps Leader
Airbus · Posted Nov 5
Commercial aircraft, helicopters, defense, and space systems manufacturing services
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About the role
The role sits within a centralized AI Product Support & Operations function supporting a high-growth AI Product/Service Line at Airbus. The team works across software engineering, site reliability, and AI/ML architectures, building intelligent diagnostic pipelines, RAG-driven knowledge tools, self-healing systems, and automated triage engines. The AIOps Leader acts as principal technical architect and lead builder, designing and executing the end-to-end automation strategy to eliminate operational toil, optimize MTTR, and build proactive anomaly detection across the AI ecosystem.
What you will do
- Self-Healing Infrastructure & Workflows: Architect, build, and deploy auto-remediation routines, script-based diagnostic runners, and event-driven automation triggers that autonomously resolve platform issues.
- LLM & RAG Systems Engineering: Design, implement, and maintain advanced Retrieval-Augmented Generation (RAG) knowledge tools, vector databases, and LLM utilities that index telemetry, historic logs, and RCAs for instant incident context.
- Bot & Agent Development: Lead the development and production rollout of conversational AI agents, custom webhooks, and self-service bots integrated into ticketing engines to automate Tier-1 and Tier-2 resolutions.
- Observability Architecture: Build enterprise-grade telemetry ingestion workflows, automated log scraping, and context-enrichment pipelines that dynamically append system metrics directly to incident tickets upon creation.
- Predictive Anomaly Detection: Configure and tune real-time predictive alerting, log-pattern analysis, and AI-driven monitoring models across AWS, Azure, or GCP microservices.
- Operational BI & Analytics: Architect and own centralized executive and operational dashboards (e.g., ServiceNow, Datadog) tracking MTTR velocity, system uptime, defect density, ticket deflection rates, and SLA/CSAT compliance.
- Toil Elimination: Continuously audit support operational bottlenecks across product teams, transforming high-volume manual intervention points into production-grade, single-click, or fully autonomous workflows.
- Log & Metadata Standardization: Standardize system log outputs, stack-trace formatting, and tagging taxonomy across all AI products to ensure platform telemetry remains machine-readable for AI engines.
- Technical Mentorship: Guide L1/L2 support engineers on best practices for automation, code-based triage, and log parsing.
Skills used in this role
What the employer is looking for
- Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Technology, or a related quantitative field.
- Overall Experience: 7+ years of hands-on experience across Software Engineering, Site Reliability Engineering (SRE), DevOps, or Systems Operations—with a focused concentration on cloud infrastructure automation and AI/ML operational tooling.
- Platform Specialization: At least 3+ years architecting and running operations directly within major cloud ecosystems (AWS or GCP), including native AI/ML compute platforms.
- AWS & GCP Native AI Platforms: Deep hands-on experience orchestrating production AI/ML workflows on AWS (Bedrock, SageMaker AI, OpenSearch, AWS Lambda) or GCP (Vertex AI, Vertex AI Agent Builder, Cloud Run, BigQuery).
- Cloud Infrastructure & Infrastructure-as-Code (IaC): Advanced experience writing and managing cloud provisioning scripts using Terraform, AWS CloudFormation, or Google Cloud Deployment Manager to deploy auto-scaling, resilient operations environments.
- Containerization & Orchestration: Production experience managing microservices via Kubernetes (EKS/GKE) and Docker to support agentic AI workers, vector indexing engines, and automated micro-tasks.
- Observability & Cloud Telemetry: Proven capability to configure full-stack observability across cloud environments using AWS CloudWatch or GCP Cloud Logging/Monitoring to trigger automated alerts and log enrichment.
- Advanced Automation & Scripting: Strong engineering capability in Python, Go, or Shell to build autonomous cloud functions (AWS Lambda/GCP Cloud Run), self-healing infrastructure scripts, and custom ITSM connectors (Jira/ServiceNow APIs).
- Enterprise Generative AI Stack: Production execution experience deploying RAG (Retrieval-Augmented Generation) architectures using cloud vector engines (Amazon Bedrock Knowledge Bases, GCP Vertex AI Search, Pinecone, or Qdrant) for automated incident context retrieval.
- Technical Leadership & Influence: Proven ability to architect complex automation systems independently, establish technical standards, and convince cross-functional teams to adopt new operational models.
- Root-Cause Obsession: Relentless drive to solve underlying architectural flaws rather than applying temporary operational workarounds.
- Cross-Functional Bridge: Ability to speak fluidly with product developers, AI researchers, enterprise clients, and technical support teams.
- Thrives in Ambiguity: Highly adaptable problem solver capable of establishing order, structure, and code standards in unstructured environments.
Preferred qualifications
- Linguistic Skill: Professional working proficiency or full fluency in French (spoken and written).
- Certifications: ITIL v5 Foundation or Managing Professional, Certified Agile Service Manager (CASM), PMP, or introductory Cloud/AI certifications (AWS Certified Cloud Practitioner, Azure AI Fundamentals).
- AI Bot Implementation Experience: Direct hands-on experience implementing conversational AI, RAG-based internal search, or auto-remediation bots within support portals.
Benefits and support
- Flexible working arrangements
About Airbus
Airbus is a global pioneer in the aerospace industry, designing, manufacturing, and delivering commercial aircraft, helicopters, defense systems, and space solutions worldwide. As a leading aeronautics and space company, it connects people and places through continuous technological innovation and advanced engineering. Headquartered in the Netherlands with operations across Europe and the globe, Airbus drives sustainable aerospace development and next-generation mobility.
- Industry
- Aerospace
- Company size
- 168000+ employees
- Founded
- 1970
- Location
- Leiden, Netherlands
- Funding stage
- Public Company
Leadership
Chief Executive Officer
Chief Financial Officer
Chief Technology Officer
Chief Sustainability Officer and Communications
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