Senior AI Solution Architect

New
Canada, Germany, India, Singapore, United Kingdom, United StatesFull-TimeSenior
Salary not disclosed
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Job Details

Languages
English
Experience
10+ years of experience in software engineering, distributed systems, or backend architecture
Required Skills
AWSDockerPythonGCPJavaKubernetesC#AzureMLOpsDistributed Systems

Requirements

  • 10+ years of experience in software engineering, distributed systems, or backend architecture.
  • 5+ years of experience designing systems that incorporate machine learning or data-driven components.
  • Strong experience architecting large-scale, production-grade software systems.
  • Deep understanding of machine learning system architecture, model deployment patterns, and ML lifecycle management.
  • Strong programming experience in Python, Java, C#, or similar languages.
  • Experience designing systems in cloud environments (AWS, Azure, or GCP).
  • Experience with containerization and orchestration technologies such as Docker and Kubernetes.
  • Strong understanding of data pipelines, distributed systems, and microservices architectures.
  • Excellent system design, problem-solving, and technical leadership skills.
  • Strong written and spoken English communication skills.
  • Degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

Responsibilities

  • Design scalable architectures for machine learning platforms, AI services, and data processing pipelines.
  • Define system-level architectures that integrate machine learning models into distributed production systems.
  • Ensure high availability, scalability, and performance of ML-powered applications.
  • Architect end-to-end ML pipelines including data ingestion, feature engineering, training workflows, model serving, and monitoring.
  • Guide teams in implementing modern MLOps practices across projects.
  • Provide architectural leadership and establish best practices for system design and observability.
  • Conduct architecture reviews and mentor engineers on building scalable ML-driven software systems.
  • Partner with client stakeholders to translate complex business requirements into scalable technical architectures.
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