AI Architect/FDE - Healthcare

Confisa International Group

12d•Hybrid

About The Position

The AI Architect/FDE will work with a healthcare client in a client-facing role combining hands-on engineering and solutioning, from pre-sales through early delivery. The position is part of the Enterprise AI Platforms & Agentic Solutions business unit at a global technology consulting and digital solutions company focused on helping enterprises scale production-grade AI adoption. The role partners with industry go-to-market teams to develop repeatable AI solutions, accelerators, and transformation programs tied to business outcomes. The position is based in New York, the Bay Area, Dallas, or Chicago, with hybrid arrangements and no fully remote option. Travel may be approximately 25% when necessary. The stated level is Manager, Principal, or Senior Principal. The position reports to the Artificial Intelligence Leader, North America.

Requirements

12+ years of overall IT experience, with 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 to improve engineering throughput, documentation, solution design, and delivery quality.
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

Lead client-facing solutioning and hands-on engineering from pre-sales through early delivery.
Design enterprise AI solutions using Google Cloud Platform, Vertex AI, and cloud-native architecture patterns.
Develop scalable backend solutions using Java, Spring Boot, microservices, REST APIs, and security patterns.
Integrate AI solutions with enterprise APIs, legacy platforms, modern platforms, and data exchange patterns.
Evaluate and apply 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.