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We are seeking a seasoned AI Solution Architect to design and lead end‑to‑end AI solutions for healthcare clients. This role requires a strong blend of AI/ML & GenAI architecture, healthcare domain knowledge, and client‑facing solutioning experience. The architect will work closely with business stakeholders, data science teams, engineering, and compliance to deliver scalable, secure, and compliant AI solutions that drive measurable business outcomes.
Responsibilities
- Design end‑to‑end AI / GenAI solution architectures covering data ingestion, feature engineering, model development, deployment, and monitoring.
- Lead solutioning for healthcare use cases such as:
- Prior Authorization & Utilization Management
- Claims processing & Payment Integrity
- Care Management & Population Health
- Clinical document processing and summarization
- Provider & member analytics
- Architect agentic AI and RAG‑based solutions using LLMs for unstructured healthcare data (clinical notes, policies, contracts, medical records).
- Translate business problems into AI‑driven architectures, ensuring alignment with ROI, scalability, and regulatory requirements.
- Define reference architectures, NFRs, and technology standards for AI platforms.
- Collaborate with data science teams on:
- Model selection and evaluation
- Prompt engineering and orchestration strategies
- Human‑in‑the‑loop (HITL) workflows
- Ensure solutions comply with HIPAA, PHI/PII, security, governance, and AI risk frameworks.
- Provide technical leadership during pre‑sales, client workshops, proposals, and solution walkthroughs.
- Mentor engineers and junior architects; review designs and ensure architectural best practices.
- Stay current with emerging trends in GenAI, agentic workflows, healthcare AI regulations, and cloud AI services.
Qualifications
Core Technical Skills
- Strong foundation in AI/ML, Deep Learning, and GenAI architectures
- Hands‑on experience with LLMs, RAG pipelines, vector databases, and AI agents
- Experience with unstructured data processing (NLP, OCR, Intelligent Document Processing)
- Solid understanding of data engineering & analytics stacks
(Data lakes, data warehouses, ETL/ELT pipelines) - Proficiency with cloud platforms (AWS / Azure / GCP) and AI services
- Experience with microservices, APIs, containerization (Docker/Kubernetes)
Healthcare Domain Expertise(Preferred)
- Knowledge of payer and provider workflows
- Exposure to regulatory and compliance requirements in healthcare
- Proven experience delivering AI solutions in healthcare operations or clinical workflows
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