Lead AI Architect

This is an internal Scania opportunity.Scania is undergoing a transformation from being a leading supplier of trucks, buses, and engines to providing complete and sustainable transport solutions. Together with TRATON and our sister brands MAN, Volkswagen Truck & Bus, and International, we are working to shape the future of mobility with innovative and environmentally conscious solutions. Our values – customer first, respect, team spirit, responsibility, and elimination of waste – are at the heart of everything we do. Together, we are at the forefront of creating a sustainable future. Role SummaryThe AI Architect shapes the architecture that enables enterprise-grade AI and agentic solutions to be built, deployed, governed, monitored, and scaled across Scania. The role designs the technical foundation for AI agents, model integration, orchestration, knowledge retrieval, memory, tool integration, model routing, security, identity, governance, observability, evaluation, and self-service capabilities. The AI Architect also guides Scania's model strategy, including when to use commercial, open-source, self-hosted, fine-tuned, or internally developed models. The role combines strong architecture expertise with deep knowledge of artificial intelligence, machine learning, and deep learning to ensure solutions are scalable, secure, maintainable, cost-effective, and aligned with Scania's long-term technology strategy. Job ResponsibilitiesAI and Platform ArchitectureDefine and evolve the end-to-end architecture for AI and agentic platforms, including agent execution, workflow orchestration, APIs, identity, governance, memory, knowledge services, observability, and evaluation.Model Strategy and ArchitectureDefine architectural approaches for commercial, open-source, self-hosted, fine-tuned, domain-specific, and internally developed AI models. Evaluate models based on quality, latency, cost, safety, explainability, data control, deployment model, and suitability for Scania use cases.AI Model Development and LifecycleGuide model development, training, fine-tuning, adaptation, evaluation, optimization, inference, and production deployment. Define standards for experimentation, dataset management, model versioning, governance, monitoring, and lifecycle management.Agentic AI ArchitectureDesign architectural patterns for AI agents, including planning, tool use, memory, multi-agent coordination, human approval, verification, guardrails, and orchestration.Knowledge and RAG ArchitectureDesign enterprise capabilities for retrieval-augmented generation and knowledge services, including ingestion, document processing, embeddings, vector and hybrid search, reranking, context building, citations, and grounding verification.Model Gateway and RoutingArchitect model gateway and routing capabilities, including provider abstraction, fallback strategies, self-hosted model support, model selection, and cost-aware routing.Reusable AI Platform ServicesDesign reusable platform capabilities such as agent execution, workflow engines, model routing, tool registries, skill execution, memory services, context building, policy enforcement, audit logging, and usage and cost tracking.Security and GovernanceEmbed security and governance throughout the AI lifecycle, including identity and access management, RBAC, policy enforcement, human approval gates, auditability, prompt-injection protection, PII handling, sandboxing, budget controls, and threat modeling.Technology Evaluation and StandardsEvaluate AI frameworks, orchestration patterns, model providers, tools, connectors, and architectural building blocks. Establish reusable architectural patterns and technical standards that support scalability, interoperability, and vendor independence.Stakeholder Management and Technical LeadershipCollaborate with Product Owners, architects, engineering teams, security, data, infrastructure, and other stakeholders to translate business and product priorities into technically feasible solutions. Communicate architectural decisions through diagrams, decision records, patterns, technical guidance, and coaching.Personal Capability BuildingMaintain deep knowledge of developments in artificial intelligence, machine learning, deep learning, agentic AI, cloud architecture, AI security, and industry best practices. Contribute to knowledge sharing and capability development across Scania. Who You AreArtificial Intelligence and Machine LearningDeep expertise in artificial intelligence, machine learning, and deep learning, including neural networks, transformers, embeddings, attention mechanisms, language models, multimodal models, classification, ranking, and generative AI.Model Development and OptimizationHands-on understanding of model development, training, fine-tuning, evaluation, optimization, deployment, model serving, inference optimization, distillation, and quantization.Agentic AI and RAGStrong understanding of agentic AI, retrieval-augmented generation, tool calling, orchestration patterns, memory, evaluation, guardrails, human-in-the-loop workflows, and AI safety.MLOps and LLMOpsStrong knowledge of experiment tracking, dataset management, model registries, evaluation pipelines, model monitoring, drift detection, lifecycle management, and production deployment.Cloud and Platform ArchitectureExperience designing AI, data, cloud, integration, or enterprise platforms, including cloud-native architecture, containerized workloads, GPU-based environments, secure runtimes, CI/CD, monitoring, tracing, and scalable infrastructure.Enterprise Identity and SecurityGood understanding of enterprise identity and access management, including Microsoft Entra ID, OAuth/OIDC, RBAC, service accounts, and permission propagation.Communication and Technical LeadershipAbility to communicate complex AI and architecture topics clearly and translate strategic requirements into reusable architectural patterns and practical technical guidance. This Is UsAI is evolving at tremendous speed. But AI itself does not create value. Value comes when we use it to change how we work, make better decisions and create better products and services for our customers.We are the AI Enablement section within Scania’s IT organisation, working to make AI a natural and scalable part of how Scania works. We combine AI expertise, technology, product ownership and enablement to help colleagues adopt AI and turn its possibilities into real value. We work across Scania, together with business teams, technology teams and external partners. Our work spans AI platforms and tools, adoption, governance, capability building and new ways of working. We help people and teams understand where AI can make a difference, build confidence in using it and translate new capabilities into everyday work. We are a diverse team with different backgrounds, expertise and perspectives, united by curiosity and a shared ambition to shape how AI is adopted and used at Scania. We actively support you in:Growing your expertise in AI, emerging technologies and AI adoptionWorking with rapidly evolving technology in a practical enterprise environmentCollaborating across business, technology and organisational boundariesExperimenting, learning and turning new AI capabilities into scalable solutions and new ways of workingBuilding a strong network across Scania and contributing to how our AI journey evolves Scania OffersWith a structured development plan and courses, Scania supports your career growth both locally and internationally. Benefits include training at our health center Gröndal or wellness allowance, result bonus, flexible hours, and company car leasing. Scania also hosts events for employees and their families, and Stockholm residents enjoy direct access to Södertälje via Scania Job express buses for an easy commute to Södertälje. ApplicationWe look forward to receiving your application, consisting of your CV and kindly ask you not to share a cover letter to ensure an efficient and unbiased recruitment process for all parties. Apply as soon as possible, no later than 2026-10-14. Screening will take place on an ongoing basis during the application period. Logical and personality tests may be used as part of the selection process, and a background check may be required for this role. We are currently recruiting for several positions within the section. By applying for this role, you may also be considered for suitable opportunities in other groups within the section. If you have questions or would like more information, please contact:Sanaz Hassanzadeh; [email protected] We look forward to your application!