AI Solutions & Delivery Specialist

Qantas Airways
Melbourne
Workplace: HybridFull timeFunction: Transportation & Fleet OperationsSkills: ["Communication","Stakeholder management","Prioritization","Working in ambiguity","Delivery focus"]

Lead AI experimentation and prototype delivery in Jetstar’s Rapid Validation Lab, driving use-case discovery through PoCs and working prototypes. Own the end-to-end classical ML lifecycle—from problem framing and feature engineering to production deployment and monitoring—while creating deployment-ready blueprints for business and technology partners. Evaluate AI platforms and partners, build a reusable internal AI agent catalogue, and support responsible AI governance, cybersecurity, privacy, and compliance.

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FursaFursa
Qantas Airways
Qantas Airways
9 hours ago

AI Solutions & Delivery Specialist

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Source: Company careers pageValidated by: Fursa AI
Last checked: 8 hours agoStatus: Live

Job Summary

Lead AI experimentation and prototype delivery in Jetstar’s Rapid Validation Lab, driving use-case discovery through PoCs and working prototypes. Own the end-to-end classical ML lifecycle—from problem framing and feature engineering to production deployment and monitoring—while creating deployment-ready blueprints for business and technology partners. Evaluate AI platforms and partners, build a reusable internal AI agent catalogue, and support responsible AI governance, cybersecurity, privacy, and compliance.
Location: Melbourne
Workplace: Hybrid
Employment Type: Full time · Permanent
Job Function: Transportation & Fleet Operations
Seniority: Mid level

Key Responsibilities

  • •Influence technical delivery of AI, agentic AI, and GenAI proof-of-concepts from discovery to working prototype.
  • •Define PoC scope, hypotheses, success measures, and exit criteria, and make evidence-based recommendations to proceed, pivot, or stop.
  • •Create deployment-ready artefacts (solution architecture documentation, agent blueprints, autonomy boundaries, and runbooks) and maintain versioned enterprise blueprints.
  • •Build and maintain a reusable internal AI agent catalogue to support repeatable experimentation and high-quality handoffs.
  • •Apply data science expertise to PoC design and evaluation, including model selection, bias assessment, performance baselines, and support responsible AI governance, privacy, and compliance.

Key Requirements

  • •Proven experience delivering AI or data-driven solutions from discovery through to validated prototype in an enterprise environment.
  • •Strong knowledge of AI/ML concepts, agentic AI architectures, large language models, and cloud-based AI services across AWS, Azure, or GCP.
  • •Experience assessing AI platforms and tools against PoC requirements, documenting clear technical findings for evaluation.
  • •Skilled in producing solution architecture artefacts, deployment process maps, and handoff-ready technical documentation.
  • •Familiarity with AI governance, responsible AI principles, and enterprise security and compliance frameworks.
Experience:Enterprise environment
Skills:CommunicationStakeholder managementPrioritizationWorking in ambiguityDelivery focus
Languages:English
Tech Stack:AWSAzureGCPPythonSnowflakeSnowparkSQLScikit-learnPandasStatsmodelsXGBoostLightGBMRAGMLOpsFeature engineeringModel validationBias and fairness assessmentStatistical analysis

Company Brief

Qantas Airways
Australia’s flag carrier providing domestic, international and freight air services, operating Qantas, Jetstar and QantasLink brands, plus a loyalty business (Qantas Frequent Flyer) and aviation services.
Industry: Airlines
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Mascot, NSW, Australia
Founded: 1920
Glassdoor
Glassdoor: 3.8
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