Senior AI/ML Solutions Architect

About the role

Join our Cause to create a person-focused and economically sustainable health care system. This is a unique technical leadership role that sits at the critical intersection of AI innovation and enterprise architecture.

Responsibilities

• Develop working prototypes to validate technical approaches, demonstrate feasibility, and build stakeholder alignment
• Write production-quality code when needed to fill gaps, solve complex problems, or establish patterns for teams to follow
• Conduct hands-on technical evaluations of emerging AI technologies, frameworks, and platforms
• Build proof-of-concepts that translate strategy into tangible demonstrations
• Establish architectural patterns for AI systems through working examples and reference implementations
• Define standards for AI-specific concerns: evaluation frameworks, observability, monitoring, safety guardrails, model governance, and responsible AI practices
• Create and maintain reference architectures for common patterns (RAG systems, agentic applications, ML pipelines)
• Lead technical design reviews and document architectural decisions
• Serve as primary liaison between Applied AI and enterprise architecture/platform engineering teams
• Translate requirements bidirectionally: AI needs to enterprise architects, enterprise constraints to AI engineers
• Advocate for AI-specific requirements within traditional architecture frameworks while ensuring alignment with Cambia's technology strategy
• Guide AI/ML portfolio decisions
• Think strategically about Applied AI's portfolio, identifying architectural patterns and reuse opportunities
• Evaluate technical feasibility and integration complexity for product roadmap decisions
• Provide recommendations balancing innovation with enterprise readiness
• Architect solutions for complex integrations involving multiple organizations and platforms
• Represent Cambia's technical interests in collaborative initiatives, building alignment through clear technical communication

Qualifications

• Hands-on technical expertise in modern AI/ML systems
• Strong coding skills in Python and experience building production AI applications, APIs, and integrations
• Practical experience with AI-specific requirements: evaluation frameworks, observability patterns, monitoring strategies, model governance, bias mitigation, and safety guardrails
• Experience with AI/ML platforms and cloud services (AWS, Azure, etc.) including hands-on implementation work
• Architecture & Integration Experience: Demonstrated architecture experience spanning business units/technology domains with ability to design solutions that work across organizational boundaries
• Proven ability to design solutions that work across organizational boundaries and complex partnership integrations
• Collaboration & Consensus Building: Exceptional consensus-building skills: brings stakeholders together through prototypes, demonstrations, and shared technical understanding
• Strong communication skills across technical domains: can explain AI system needs to infrastructure teams and enterprise constraints to AI engineers
• Leadership: Strategic thinking about product portfolios: can see patterns across multiple AI initiatives and identify opportunities for reuse and standardization
• Mentoring ability with engineers and architects, helping teams grow their technical capabilities
• Strong interpersonal skills: relates well to people across all organizational levels and establishes trust through genuine collaboration

What You Will Do

• Build & Prototype
• Develop working prototypes to validate technical approaches, demonstrate feasibility, and build stakeholder alignment
• Write production-quality code when needed to fill gaps, solve complex problems, or establish patterns for teams to follow
• Conduct hands-on technical evaluations of emerging AI technologies, frameworks, and platforms
• Build proof-of-concepts that translate strategy into tangible demonstrations
• Shape AI Architecture Standards
• Establish architectural patterns for AI systems through working examples and reference implementations
• Define standards for AI-specific concerns: evaluation frameworks, observability, monitoring, safety guardrails, model governance, and responsible AI practices
• Create and maintain reference architectures for common patterns (RAG systems, agentic applications, ML pipelines)
• Lead technical design reviews and document architectural decisions
• Bridge AI and Enterprise Architecture
• Serve as primary liaison between Applied AI and enterprise architecture/platform engineering teams
• Translate requirements bidirectionally: AI needs to enterprise architects, enterprise constraints to AI engineers
• Advocate for AI-specific requirements within traditional architecture frameworks while ensuring alignment with Cambia's technology strategy
• Guide AI/ML Portfolio Decisions
• Think strategically about Applied AI's portfolio, identifying architectural patterns and reuse opportunities
• Evaluate technical feasibility and integration complexity for product roadmap decisions
• Provide recommendations balancing innovation with enterprise readiness
• Architect solutions for complex integrations involving multiple organizations and platforms
• Represent Cambia's technical interests in collaborative initiatives, building alignment through clear technical communication