Data Analytics and AI Engineer

2 days ago

Singapore beBeeCloudEngineer Full time

Job Summary

We are seeking a highly skilled Data Analytics and AI Engineer to join our team. As a key member of our cloud platform team, you will play a critical role in helping customers transform their business using technology built in the cloud.

About the Role

You will work closely with technical sales teams as a data analytics and Artificial Intelligence expert to showcase Google Cloud's value. You will design solutions, conduct proofs-of-concept, and resolve technical issues related to data migrations and lifecycle management. Your goal will be to understand customer needs, present tailored solutions, and demonstrate technical and communication skills while working with a team of experts that fosters equal opportunities for success.

Key Responsibilities

  • Design and implement end-to-end data solutions covering ingestion, storage, processing, and advanced analytics, ensuring seamless integration with existing systems.
  • Guide customers in building and integrating collaborative AI agents using tools like Vertex AI agent engine and Agent Development Kit (ADK), ensuring solutions meet technical requirements and deliver tangible business outcomes.
  • Identify opportunities where AI agents can automate tasks, enhance decision-making, and create value, ensuring solutions are technically sound and impactful.
  • Communicate complex architectural concepts effectively to technical stakeholders and executive leadership, showcasing Google Cloud's data and AI offerings address and unlock new possibilities.

Requirements

  • Bachelor's degree or equivalent practical experience.
  • 10 years of experience with cloud native architecture in a customer-facing or support role.
  • Proven experience with practical application and architectural considerations of AI/ML, including Machine Learning (ML) lifecycle, ML frameworks, and MLOps principles.
  • Hands-on experience in developing data warehouses, data lakes, batch/real-time event processing, streaming, data processing, and data governance on cloud native architectures.

Preferred Qualifications

  • Experience implementing MLOps best practices, CI/CD pipelines for ML models, and infrastructure as code for deploying data and AI solutions.
  • Experience in integrating data and AI solutions with existing enterprise systems, on-premises infrastructure, and third-party applications.
  • Experience optimizing performance, cost-efficiency, and scalability of large-scale data processing pipelines and ML inference systems.
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