Saab

AI Solution Architect – Digital Solutions

Saab

full-time

Posted on:

Location Type: Hybrid

Location: Linköping • Sweden

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Tech Stack

ApacheAWSAzureCloudDockerJavaKafkaKubernetesMicroservicesPythonPyTorchScikit-LearnSparkTensorflow

About the role

  • Design and architect scalable, secure, and reliable AI infrastructure using microservices, API gateways, and serverless architecture patterns
  • Lead the end-to-end delivery of AI solutions from requirements and system design through to deployment and monitoring in production environments
  • Build and maintain CI/CD pipelines, containerised deployments (Docker, Kubernetes), and model tracking workflows using e.g. MLflow
  • Develop and expose AI capabilities through robust API services, integrating ML models into existing platforms and enterprise systems
  • Apply hands-on expertise in ML/DL frameworks
  • Leverage cloud AI services across AWS and/or Microsoft Azure to architect cost-effective and performant solutions
  • Manage and process large-scale data using Spark or Kafka, ensuring robust data engineering practices
  • Ensure data governance, privacy compliance and security best practices are embedded into every solution
  • Align AI initiatives with business strategy, contributing to vendor selection, cost optimisation, and technology roadmap decisions
  • Communicate complex AI architectures and trade-offs clearly to both technical teams and executive stakeholders
  • Collaborate cross-functionally with data scientists, ML engineers, solution owners, and domain experts to deliver outcomes that matter

Requirements

  • 3–7 years of experience in AI, ML, or data science roles
  • A minimum of a Bachelor's degree in Computer Science, Data Science, Software Engineering, Mathematics, or a related field
  • Strong proficiency in Python; solid working knowledge of Java and/or C++ for high-performance applications
  • Practical experience with ML/DL frameworks: TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers
  • Proven MLOps skills including CI/CD pipeline design, Docker, Kubernetes, model tracking, and API development
  • Experience with large-scale data engineering tools such as Apache Spark or Kafka
  • Solid understanding of cloud AI platforms (AWS, Azure) and associated AI/ML services
  • Knowledge of data governance principles and compliance with privacy regulations
  • Excellent communication skills
  • Strong project management abilities and a track record of effective stakeholder management
  • Outcome-oriented mindset with a focus on delivering measurable business value
Benefits
  • Flexible hybrid work model
  • Competitive salary
  • Comprehensive benefits package
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
AI infrastructure designmicroservicesAPI gatewaysserverless architectureCI/CD pipelinesDockerKubernetesMLflowPythonMLOps
Soft Skills
communication skillsproject managementstakeholder managementcollaborationoutcome-oriented mindset
Certifications
Bachelor's degree in Computer ScienceBachelor's degree in Data ScienceBachelor's degree in Software EngineeringBachelor's degree in Mathematics