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Metro generalist senior engineer role with broad cloud/AI requirements and recognizable multinational brand.
Cloud architecture plus MLOps/GenAI requirements moderately restrict cross-industry portability.
Explicit 6+ years requirement plus mandatory cloud, Kubernetes, and MLOps/GenAI expertise.
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Lead design and development of scalable cloud-native platforms and AI-driven production solutions.
Architect distributed microservices systems with strong DevOps/MLOps practices including CI/CD, containerization (Docker/Kubernetes), and observability.
Own cloud architecture, deployment strategies (blue-green, canary), and mentor engineering teams across AWS/GCP/Azure environments.
6+ years of relevant experience in software/cloud engineering roles.
Bachelor's or Master's degree in Computer Science, Engineering, or related field.
Proven experience with cloud platforms (AWS/GCP/Azure), microservices architecture, Docker, Kubernetes, CI/CD, and DevOps.
Hands-on experience building AI/ML or Generative AI solutions (LLMs, RAG pipelines, vector databases) and implementing MLOps including model lifecycle management.
Senior engineer proficient in designing and operating enterprise-grade distributed cloud-native applications with AI/ML integrations.
Experienced in end-to-end cloud architecture ownership including security, compliance, cost optimization, and high availability.
Capable of leading cross-functional teams and mentoring junior engineers with focus on best engineering practices and modern deployment strategies.