AI Solutions Architect (GCP) @ NY/Remote

Remote, USA Full-time
Title: AI Solutions Architect (GCP) Location: New York, NY (Onsite, may consider remote for strong candidates) Study Level : Bachelor's Degree Skill Cluster : Data-GCP Vertex AI. Primary Skill : LLMs, AI/ML, Vertex AI Experience : 15+ years Job Description : The AI Solutions Architect defines the technical direction for AI, ML, and data-driven capabilities across the enterprise. The role shapes the architecture for intelligent, cloud-native solutions leveraging machine learning, LLMs, automation, and modern data platforms while ensuring security, scalability, compliance, and operational resilience. Key Responsibilities: • Architecture & Strategy spanning data pipelines, training workflows, inference layers, and governance. • Translate business priorities into AI-enabled solution designs and reusable reference architectures. , MLOps workflows, and cost efficiency across AI workloads. • Maintain and evolve architecture standards; champion adoption across delivery teams. • Leadership & Influence . Mentor engineering teams and contribute to architecture communities of practice. Qualifications Required: • Bachelors degree in Computer Science or related field. • 15+ years in software architecture with strong experience in distributed systems. • 5+ years designing or implementing AI/ML or LLM-based solutions. • 5+ years hands-on development experience (Java/Kotlin/C#/Python). • Expertise in cloud native architecture, APIs, microservices, and event-driven platforms. • Strong understanding of AI security, model governance, and data privacy controls. • Experience with data pipelines, databases, and high scale systems. Preferred: • Masters degree or equivalent experience. • Experience with GCP (Vertex AI, BigQuery) and Kubernetes. • Familiarity with orchestration frameworks, vector databases, embeddings, and model gateways Mandatory Skills: • Design end-to-end architectures for AI/ML and LLM-based solutions, spanning data pipelines, training workflows, inference layers, and governance. • Translate business priorities into AI-enabled solution designs and reusable reference architectures. • Evaluate emerging AI and cloud capabilities and guide technology adoption aligned with enterprise strategy. • Engage early with the Governance organization to align on standards, secure required approvals, and deliver the architecture artifacts needed to support enterprise-grade solution decisions Apply tot his job
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