We are looking for a Senior AI Solutions Architect to lead the delivery of advanced AI and machine learning solutions. This role combines deep technical execution with architectural leadership, helping move promising concepts into stable, production-ready applications that support critical business operations. You will collaborate with senior AI and engineering leaders to design scalable systems, guide implementation decisions, and ensure solutions create measurable operational and commercial value.

This role is 100% Remote.

Responsibilities:

• Design and lead the end-to-end architecture of AI and ML solutions, taking initiatives from early experimentation through reliable production deployment.
• Partner with AI leadership and cross-functional engineering teams to align technical roadmaps with business priorities and operational goals.
• Build, evaluate, and optimize machine learning models and AI-powered applications for high-availability environments serving large user populations.
• Establish robust MLOps and DevOps practices, including model tracking, containerization, orchestration, automated testing, and deployment pipelines.
• Select and integrate appropriate cloud, data, and infrastructure services across platforms such as Azure, AWS, and Google Cloud to support scalable AI workloads.
• Guide the development of data pipelines and platform components using technologies such as Kafka, Spark, SQL, and NoSQL systems to enable dependable model performance.
• Apply methods such as large language models, fine-tuning, privacy-aware AI techniques, and optimization approaches to solve complex operational challenges.
• Provide technical leadership through influence and credibility, helping stakeholders understand solution design, adoption considerations, and implementation impacts.
• At least 7 years of progressively senior experience delivering AI, machine learning, or automation solutions, including a minimum of 3 years deploying models in live production environments.
• Demonstrated success building AI-enabled systems for high-uptime, mission-critical products used by hundreds or thousands of users.
• Strong programming expertise in Python and experience with at least two additional languages such as C#, C/C++, Java, or Go.
• Hands-on knowledge of modern AI and machine learning frameworks, including tools such as PyTorch, TensorFlow, Scikit-learn, Transformers, or similar technologies.
• Practical experience with MLOps, containerization, orchestration, and CI/CD practices using technologies such as Docker, Kubernetes, MLflow, Kubeflow, and related toolsets.
• Familiarity with cloud AI and infrastructure services across one or more major platforms, including Microsoft Azure, Amazon Web Services, and Google Cloud Platform.
• Experience working in complex regulated or operationally intensive sectors such as logistics, transportation, healthcare, defence, manufacturing, or comparable industries.
• Ability to communicate architectural decisions clearly and lead technical direction through collaboration, influence, and stakeholder engagement.

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