Director overseeing Integrated Cloud Consulting at RSM, spearheading cloud solutions for various clients. Leading a team and driving growth in cloud practices across industries.
About the role
- AI Solution Architect at Saab designing and deploying scalable AI systems in the defence sector. Leading delivery of AI solutions and collaborating with cross-functional teams.
Responsibilities
- 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
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
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