AI Architect/FDE - Healthcare

CONFISA INTERNATIONAL GROUP•New York, NY

10d•Hybrid

About The Position

The AI Architect/FDE is a client-facing, hands-on engineering and solutioning role supporting a healthcare client, spanning pre-sales through early delivery. The position sits within the Enterprise AI Platforms & Agentic Solutions business unit and focuses on cloud architecture, enterprise integration, and generative AI solutions. The company’s Enterprise AI business helps organizations scale AI adoption through functional consulting, an AI Foundry, and agentic AI platforms, with solutions aligned to business outcomes. The role is based in a major U.S. hub, with hybrid arrangements available in New York, the Bay Area, Dallas, or Chicago; fully remote work is not available. Travel may be approximately 25% when necessary. The stated level is Manager, Principal, or Senior Principal, and the position reports to the Artificial Intelligence Leader, North America.

Requirements

12+ years of overall IT experience, including significant experience in cloud architecture, enterprise architecture, integration, or AI/ML solution architecture.
Strong hands-on experience with Google Cloud Platform services and cloud-native architecture patterns.
Deep understanding of Vertex AI, generative AI solution design, prompt engineering, model integration, AI governance, and production deployment considerations.
Strong Java and Spring Boot background, including microservices architecture, REST APIs, security patterns, and scalable backend design.
Practical experience with enterprise integration, API-led connectivity, data exchange patterns, and integration with legacy and modern platforms.
Ability to evaluate and apply AI productivity tools such as Claude and Antigravity.
Experience working with senior business and technology stakeholders in complex enterprise environments.
Excellent communication, facilitation, consulting, and stakeholder-management skills.

Nice To Haves

Google Professional Cloud Architect certification or a relevant Google Cloud certification.
Experience in healthcare, provider systems, clinical operations, payer/provider integration, or regulated enterprise environments.
Experience with AI governance, security, privacy, responsible AI practices, and data-protection requirements.
Exposure to MLOps, LLMOps, CI/CD, observability, and production support models for AI-enabled platforms.

Responsibilities

Provide client-facing, hands-on engineering and solutioning from pre-sales through early delivery.
Design cloud-native and enterprise AI solutions using Google Cloud Platform and Vertex AI.
Develop generative AI solution designs, including prompt engineering, model integration, governance, and production deployment considerations.
Apply Java, Spring Boot, microservices, REST APIs, security patterns, and scalable backend design to enterprise solutions.
Design enterprise integration and API-led connectivity across legacy and modern platforms.
Evaluate and use AI productivity tools such as Claude and Antigravity to improve engineering throughput, documentation, solution design, and delivery quality.
Work with senior business and technology stakeholders in complex enterprise environments.