GCP AI Architect

What you'll do

• Design scalable, modular Generative AI architectures for production use.
• Implement RAG architectures, vector databases, and multi-agent workflow orchestrations.
• Integrate GenAI capabilities into customer-facing and internal products.
• Build data pipelines for unstructured data processing, document ingestion, and chunking.
• Manage MLOps practices including model versioning, deployment pipelines, and drift detection.
• Deploy and manage containerized applications using Kubernetes and CI/CD pipelines.
• Implement AI security guardrails, content filters, and responsible AI policy enforcement.
• Optimize model inference for low latency and cost-control strategies.

What we're looking for

• Strong understanding of Generative AI models, including LLMs, multimodal models, and embeddings.
• Hands-on experience with foundation models and model adaptation techniques.
• Expertise in prompt engineering, prompt orchestration, and agent-based frameworks.
• Ability to design scalable, modular GenAI architectures using RAG, vector databases, and multi-agent systems.
• Proficiency in data pipelines, feature engineering, and unstructured data processing.
• Strong experience in cloud-native environments (GCP) and MLOps practices including model versioning and CI/CD.
• Experience with containerization, Kubernetes, and inference optimization.