AI Solutions Architect

Rochester Regional Health

1d • $120,000 - $145,000 • Hybrid

About The Position

Architect, design, and guide delivery of AI solutions as part of Rochester Regional Health’s enterprise AI initiative, managing and leveraging platforms such as Microsoft Copilot and Microsoft Foundry, while also being familiar with capabilities from Epic, Workday, Snowflake and others to accelerate adoption and governance. Champion best practices in architecture, risk management, and program oversight, while mentoring team members and aligning technical strategy with organizational goals. Ensure all implementations are secure, reliable, ethically responsible, and compliant with healthcare regulations (HIPAA). Partner with data, engineering, security, and clinical teams to move from use-case discovery to production deployment and scale, delivering measurable value in improved care quality, operational efficiency, and patient experience.

Requirements

• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field.
• 5+ years in Solutions Architecture/Engineering with enterprise production deployments.

Nice To Haves

• Graduate degree in CS/AI/ML
• Certifications (e.g., Azure/AWS Architect, Snowflake, Kubernetes).
• Experience with LLM ecosystems (prompt engineering, retrieval‑augmented generation, guardrails), AI agents, agentic platforms, and/or NLP in healthcare.
• Familiarity with EHR platforms and standards (FHIR, HL7), and clinical safety review processes.
• Familiarity with or contributions to open‑source AI tooling or internal reusable frameworks.
• Proven ability to implement solutions in regulated environments; strong grasp of governance, security controls, and healthcare interoperability.
• Excellent systems thinking, documentation, and stakeholder communication skills.
• Hands‑on experience with cloud (Azure/AWS/GCP), data platforms (SQL/NoSQL, lakehouse), MLOps (CI/CD for models, feature stores), and secure API integration.

Responsibilities

• Architecture & design: Define target architectures for data, model, and application layers; select tooling (MLOps, vector stores, model management, observability) and integration patterns with EHR/enterprise systems.
• Use‑case delivery: Lead end‑to‑end solutioning for priority use‑cases (e.g., IT support, clinical documentation assistance, patient safety and quality); author reference implementations and reusable components.
• Security, privacy & compliance: Implement PHI safeguards, role‑based access, model governance, prompt/content filtering, audit trails; align with HIPAA and internal policies.
• Reliability & monitoring: Establish model risk controls (drift, bias, hallucination mitigation), human‑in‑the‑loop checkpoints, and performance SLAs.
• Standards & enablement: Publish architecture standards and patterns; mentor engineers and analysts; contribute to AI intake, feasibility, and TCO assessments.
• Vendor/platform evaluation: Assess AI platforms and partners; drive technical due diligence and integration plans; optimize cost/performance.
• Stakeholder engagement: Translate clinical/operational needs into technical solutions; communicate tradeoffs, roadmaps, and outcome metrics.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level