We are seeking a high-caliber Principal / Lead Cloud AI Solutions Engineer with deep expertise in Google Cloud Platform (GCP) and modern Enterprise AI paradigms. In this hybrid hands-on and customer-facing role, you will lead the architecture, design, and deployment of scalable microservices, distributed systems, and cutting-edge GenAI/Agentic solutions.
You will own the complete solution lifecycle—from direct client discovery and architectural design to hands-on implementation and production deployment—translating complex, ambiguous business problems into secure, high-performance Cloud AI systems.
Requirements
• Core Development Track (Python or Java)
Solid, hands-on enterprise-level expertise in EITHER Python OR Java (Tracks are evaluated separately; expertise in at least one is mandatory).
Proven track record building enterprise microservices, REST APIs, and distributed event-driven applications.
• Technical & Cloud Architecture
Deep technical knowledge of distributed system design, enterprise application integration,
and relational/non-relational database technologies.
Advanced expertise in Google Cloud Platform (GCP) core services: Google Cloud Run, GKE, Cloud Functions, BigQuery, and Pub/Sub.
Production experience with Docker, Kubernetes, infrastructure-as-code, and enterprise CI/CD automation pipelines.
• GCP AI & Machine Learning Ecosystem
Hands-on proficiency in building and deploying models via Vertex AI and integrating foundation models via the Gemini API.
Demonstrated experience constructing end-to-end Retrieval-Augmented Generation (RAG) systems and configuring Vertex AI Vector Search for embeddings and semantic search.
Practical experience designing agentic AI workflows and establishing automated evaluation metrics (“evals”) for enterprise AI applications.
• Client & Leadership Capabilities
Experience in customer-facing roles, driving technical discovery, solutioning, and executive-level technical discussions.