Role Type: Client-facing, hands-on engineering + solutioning (pre-sales through early delivery)
Location: Major US hub (e.g., New York, Bay Area, Dallas, Chicago – flexible for the right candidate).
Hybrid arrangements and travel: This remain hybrid opportunities in New York, the Bay Area, Dallas, or Chicago, with no fully remote option. Travel may be approximately 25%, when necessary.
Level: Manager/Principal/Senior Principal
Business Unit: Enterprise AI Platforms & Agentic Solutions
Reporting to: Artificial Intelligence Leader, North America
Company Overview:
Global technology consulting and digital solutions company that enables enterprises across industries to reimagine how they operate, compete, and grow. By combining deep domain knowledge, advanced engineering, and transformation expertise, delivers measurable business impact at scale.
Enterprise AI business unit, purpose built to help organizations move beyond pilots into scaled, product iongrade AI adoption, functional consulting, an AI Foundry, and agentic AI platforms to deliver integrated solutions that transform how work gets done across the enterprise.Operating across Banking, Insurance, Manufacturing, Retail/CPG, Energy & Utilities, Travel & Hospitality, HiTech, and Media, works closely with industry GTM teams to create repeatable AI solutions, accelerators, and transformation programs aligned to real business outcomes.
Must Have:
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.
Preferred Qualifications:
Google Professional Cloud Architect or 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.
Benefits
Comprehensive Medical Plan Covering Medical, Dental, Vision
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