AI Architect

We are seeking an experienced AI Architect to design and guide the implementation of secure, scalable, and production-ready artificial intelligence solutions. This role will establish enterprise AI architecture, lead technical design decisions, and support the delivery of machine learning and generative AI capabilities across cloud and enterprise environments.

The ideal candidate combines strong architecture and software engineering experience with hands-on knowledge of large language models, retrieval-augmented generation, AI governance, cloud platforms, and enterprise application integration.

Key Responsibilities

AI Solution Architecture and Delivery

• Design end-to-end architectures for machine learning and generative AI solutions.
• Lead the architecture and implementation of solutions involving large language models, retrieval-augmented generation, intelligent document processing, automation, and predictive analytics.
• Define reusable architectural patterns, reference architectures, and technical standards for enterprise AI.
• Guide engineering teams in developing, testing, deploying, and maintaining AI solutions that support clinical, operational, and administrative use cases.
• Evaluate emerging AI technologies and recommend appropriate platforms, models, tools, and implementation approaches.

Enterprise AI Infrastructure

• Design and optimize enterprise AI infrastructure across cloud and hybrid environments.
• Define architectural requirements for scalability, availability, security, reliability, and performance.
• Establish deployment, monitoring, and operational standards for AI workloads.
• Support platform health, system performance, capacity planning, and infrastructure readiness.
• Collaborate with cloud, infrastructure, security, data, and application teams to ensure architectural alignment.

Enterprise Systems Integration

• Design integration patterns connecting AI capabilities with enterprise applications, data platforms, healthcare systems, and business workflows.
• Define secure interfaces, APIs, data pipelines, and orchestration patterns for AI-enabled solutions.
• Partner with business and technical teams to understand system dependencies and integration requirements.
• Support implementation teams in resolving complex integration and architectural challenges.

AI Governance, Security, and Responsible AI

• Establish AI quality, safety, security, privacy, and governance standards.
• Define evaluation frameworks, testing approaches, validation methods, and monitoring requirements for AI solutions.
• Ensure solutions comply with organizational policies, regulatory requirements, and responsible AI principles.
• Identify and mitigate technical, operational, security, privacy, and model-related risks.
• Incorporate human oversight, traceability, and appropriate controls into AI solution designs.

Technical Leadership and Stakeholder Partnership

• Serve as a technical subject matter expert supporting AI strategy, adoption, and solution implementation.
• Translate complex technical concepts into clear recommendations for business and executive stakeholders.
• Lead architectural reviews and provide technical direction to engineering and delivery teams.
• Evaluate emerging AI technologies and provide implementation guidance.
• Present findings, recommendations, architectural decisions, and solution options to technical and nontechnical audiences.
• Collaborate across clinical, operational, technical, security, compliance, and executive teams.

Required Qualifications

Education

• Bachelor’s degree in Computer Science, Data Science, Software Engineering, Information Technology, Engineering, or a related field.
• Equivalent combinations of education, relevant certifications, and professional experience may be considered.

Experience

• Minimum of 5 years of professional experience in AI, machine learning, software engineering, data engineering, solution architecture, or a closely related field.
• Demonstrated experience designing and implementing enterprise-scale AI or machine learning solutions.
• Experience developing solutions using Python and modern software engineering practices.
• Experience with cloud-based AI services and infrastructure, including Microsoft Azure or Amazon Web Services, and Databricks.
• Experience with generative AI technologies, large language models, prompt engineering, and retrieval-augmented generation.
• Experience integrating AI capabilities with enterpris…