Description

You will design and scale generative AI platforms for industrial enterprises, leveraging Google Gemini and Vertex AI to solve complex manufacturing challenges.

Responsibilities

• Architect end-to-end Generative AI solutions, including Retrieval-Augmented Generation (RAG) pipelines and multi-agent systems.
• Integrate Gemini Pro and Ultra models into enterprise applications, managing fine-tuning, evaluation, and inference optimization.
• Implement AI guardrails to ensure security, data privacy, and compliance within AI workflows.
• Lead hands-on development of Proofs of Concept (PoCs) and Minimum Viable Products (MVPs) to validate designs.
• Provide technical leadership to data scientists and AI developers, guiding prompt engineering and tool evaluation.

Required Skills

• 6+ years in solutions architecture, AI/ML engineering, or technical consulting.
• 1–2+ years of hands-on experience with LLMs and Generative AI in production.
• Deep knowledge of Vertex AI, Python, BigQuery, and Google Kubernetes Engine (GKE).
• Strong proficiency with Google Cloud Platform (GCP) and infrastructure-as-code using Terraform.
• Experience with vector databases and prompt engineering strategies.
• Google Cloud Professional Certifications (e.g., Cloud Architect or Machine Learning Engineer).
• Manufacturing domain expertise and ability to advise C-level stakeholders on AI roadmaps and ROI.

Key Skills

Education

Any Graduate