Healthcare AI Solutions Architect — Remote

NTT DATA, Inc.

Plano (TX)

On-site

USD 119,578 - 221,625

Full time

14 days+

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Job summary

NTT DATA Services is seeking an experienced AI Solutions Architect to design and deliver AI, ML, and generative AI solutions for healthcare providers across North America, including hospitals, academic medical centers, physician groups, and delivery networks.

You will partner with clinical, operational, and IT leaders to translate provider challenges into scalable AI-enabled outcomes, lead reference architectures on cloud platforms and EHR integrations, and ensure responsible AI practices

Qualifications

8+ years of experience in technology architecture, data architecture, analytics, AI/ML, or healthcare technology consulting.
4+ years of experience supporting healthcare providers, health systems, hospitals, or integrated delivery networks.

Responsibilities

Design end-to-end AI and generative AI solutions for provider use cases, including architecture, data flows, integration patterns, model selection, workflow integration, governance, security, and deployment approach.
Lead solutioning for provider-specific domains such as electronic health records, clinical documentation, patient access, scheduling, revenue cycle, coding, billing, denials management, care coordination, population health, quality reporting, command centers, and patient engagement.
Develop reference architectures using cloud platforms, EHR integration services, data lakes, warehouses, lakehouses, MLOps pipelines, APIs, interoperability layers, workflow tools, and enterprise integration patterns.
Guide teams on applying large language models, retrieval-augmented generation, predictive analytics, natural language processing, computer vision, intelligent automation, and decision support in healthcare delivery settings.
Collaborate with data scientists, engineers, clinicians, informaticists, compliance teams, security architects, revenue cycle leaders, and delivery teams to move concepts from prototype to production.
Define responsible AI controls, including model monitoring, explainability, clinical safety review, human-in-the-loop validation, bias assessment, auditability, privacy, cybersecurity, and regulatory compliance.
Support pre-sales and client advisory activities, including solution presentations, proposals, estimates, demos, workshops, executive briefings, and innovation strategy sessions.
Evaluate vendor platforms and AI tools across EHR ecosystems, cloud, clinical documentation, revenue cycle, patient engagement, workflow automation, and analytics.
Create reusable assets, including provider AI solution blueprints, architecture patterns, implementation playbooks, data requirements, governance frameworks, and value case templates.