AI Architect

2 days ago

Bengaluru, Karnataka, India beBeeArchitect Full time ₹ 20,00,000 - ₹ 25,00,000
Job Description:

We are seeking an experienced architect to lead the development of cloud-native capabilities, enabling data scientists to focus on model development and delivering cutting-edge intelligent solutions. The successful candidate will drive and own the delivery of AI platforms from design and architecture to production.

This role requires a deep understanding of AI engineering and the ability to build Wayfair's next-generation AI capabilities. The ideal candidate will be responsible for designing scalable systems using Python, Go, Kubernetes, GCP, Airflow, and other technologies to support AI workloads.

The selected individual will champion open-source solutions and Google Cloud native technologies, applying them to AI use cases. They will develop end-to-end AI solutions that can power the full range of AI initiatives at Wayfair and partner with product leaders to understand technical pain points for data scientists and other teams building AI applications.

Required Skills and Qualifications:
  • 10+ years of experience in software engineering and designing systems at scale
  • ~4+ years of experience in Linux-based development, Python/Go development, and leading engineering teams
  • Experience developing AI/ML pipelines, model deployment systems, and orchestrating AI workloads with Kubernetes
  • Strong understanding of containerization, AI system scalability challenges, and software engineering best practices
  • Experience with AI/ML frameworks (TensorFlow, PyTorch) and model serving technologies
  • Knowledge of AI system monitoring, performance optimization, and model lifecycle management
  • Excellent communication skills with demonstrated experience driving teams and influencing technical decisions aligned with company AI strategy
Benefits:
  • Mix of start-up and large-company experience working on AI solutions
  • Familiarity with AI platforms (opensource or offered by Google Cloud) and how to implement them on a large scale
  • Knowledge of vector databases, embedding systems, or real-time AI inference optimization

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