AI Solution Architect

About the role

We are looking for an AI Solution Architect to join our team and lead the design, delivery and operationalisation of AI-enabled systems. You will work across engineering, data and product teams to translate business needs into scalable, secure and maintainable AI solutions. The role involves hands-on architecture, technical leadership and close collaboration with stakeholders to ensure responsible, performant and production-ready AI services.

Key responsibilities

• Define end-to-end architecture for AI solutions, including data ingestion, feature engineering, model training, serving, monitoring and lifecycle management.

• Collaborate with data engineers, ML engineers, software engineers and product owners to convert requirements into technical designs and delivery plans.

• Design robust MLOps/AI Ops practices: CI/CD for models and data pipelines, model versioning, automated testing and reproducible experiments.

• Specify and implement scalable serving architectures for real-time and batch inference, ensuring latency, throughput and cost requirements are met.

• Drive secure and compliant AI deployments, incorporating privacy-by-design, data governance, access controls and explainability where relevant.

• Establish monitoring, alerting and observability for model performance, data drift and system health.

• Provide technical guidance, review designs and mentor engineers to raise capability across the organisation.

• Evaluate and recommend AI frameworks, platforms and cloud services to meet project and platform goals.

• Help define reusable platform components, APIs and integration patterns to accelerate AI development across teams.

About you

• Proven experience architecting and delivering AI/ML systems in production, working across data, ML and software engineering domains.

• Strong understanding of ML lifecycle, MLOps practices and tooling (CI/CD, model registry, experiment tracking, automated testing).

• Hands-on experience with cloud ML and data platforms (e.g. Azure ML, AWS SageMaker, GCP AI Platform) and their managed services.

• Practical knowledge of serving architectures for batch and real-time inference, containerisation (Docker), orchestration (Kubernetes) and serverless patterns.

• Familiarity with common ML frameworks (TensorFlow, PyTorch, scikit-learn) and data processing tools (Spark, pandas, SQL).

• Good understanding of security, privacy and governance considerations for ML workflows, including data handling, access control and model explainability.

• Excellent communication skills and ability to work with cross-functional stakeholders to align technical choices with business needs.

• Experience creating architecture artefacts: diagrams, decision records, non-functional requirement specifications and runbooks.

• Fluent in English. Swedish language skills are meritorious but not required.

Nice to have

• Experience with infrastructure-as-code (Terraform, ARM/Bicep) and GitOps approaches.

• Familiarity with data platform patterns such as lakehouse, data mesh or modular data platforms.

• Knowledge of model governance frameworks and regulatory requirements relevant to AI.

• Experience working in regulated or safety-critical domains.

What we offer

• Meaningful assignments where your architecture decisions shape how AI is used across the organisation.

• Collaborative, engineering-driven culture with focus on craftsmanship and long-term value.

• Opportunity to influence platform strategy and build reusable components used by multiple teams.

• Flexible working arrangements and support for continuous learning and professional development.

Technologies and tools you may work with

• Cloud platforms: Azure, AWS or GCP

• Model training and serving: Azure ML, SageMaker, Kubernetes, Docker

• Data and processing: Databricks, Spark, Delta Lake, SQL

• MLOps and CI/CD: MLflow, Kubeflow, GitHub Actions, Azure DevOps

• Infrastructure as code & orchestration: Terraform, Helm

• Programming: Python, SQL

Why Yora

Yora is built on freedom, trust, and technical excellence. We prioritize competence over titles and long-term value over quick fixes. Our focus is on strong engineering craftsmanship, meaningful assignments, and giving our engineers the conditions they need to deliver high-quality work, without unnecessary bureaucracy. If you’re excited about building large-scale backend systems, distributed architectures, and high-impact cloud services, you’ll thrive here.