AI Solutions Architect

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:
• 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
• 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 .

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)
• 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