Remote Senior Solutions Consultant - Oncology

Job Description

One of our leading healthcare clients is looking for a Chief Solutions Architect to lead end‑to‑end architecture and solution strategy for our oncology portfolio. You’ll define and govern reference architectures spanning EMR/EHR and Revenue Cycle Management (RCM), integration middleware, cloud & data center platforms, and AI/ML solutions that drive clinical outcomes, operational efficiency, and regulatory compliance. You’ll be the go‑to authority partnering with Product, Engineering, Security, Clinical, and Go‑to‑Market teams to deliver scalable, secure, interoperable solutions.

Own the multi‑year enterprise and solutions architecture roadmap for oncology products and services (clinical, operational, financial).

Establish reference architectures and patterns for EMR/RCM interoperability, integration middleware, microservices, event‑driven systems, data/analytics, and AI/ML.

Drive cloud strategy (e.g., Azure/AWS/GCP), hybrid infrastructure, and modernization of data center workloads; ensure resiliency, performance, and cost governance (Fin Ops).

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances.

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• 8+ years in enterprise/solution architecture with experience in healthcare, including oncology domain exposure.
• Deep experience with EMR/EHR or RCM solutioning and production grade integrations
• Proven leadership across integration of healthcare systems (patient care, LIS, pharmacy, RCM, EMR, EHR)
• Hands on architecture for AI/ML use cases in healthcare, including MLOps and model governance.
• Track record of delivering large scale, highly available systems (HA/DR, autoscaling, multi region) with cost and performance guardrails.