Enterprise Architect – AI & Mythos

Solü is seeking an Enterprise Architect – AI & Mythos to support enterprise-wide AI strategy and architecture. This role is responsible for defining the target-state architecture for the organization’s core AI platform, establishing standards, governance frameworks, and reusable patterns that enable scalable, secure, and compliant AI adoption across the enterprise.

The ideal candidate will have deep experience in enterprise architecture, AI platforms, and cloud technologies, with the ability to translate strategy into technical standards and architectural roadmaps. This role partners closely with senior leadership, engineering, security, and data teams to ensure AI solutions are scalable, cost-effective, and aligned with enterprise risk and regulatory requirements.

Responsibilities

• Define and lead the enterprise architecture for the core AI platform (Mythos), including conceptual, logical, and high-level physical architecture.
• Own the target-state architecture for enterprise AI capabilities embedded across business applications.
• Establish enterprise standards, control frameworks, and reusable architecture patterns for AI platform services.
• Define governance frameworks for AI usage, including model access, lifecycle management, guardrails, and compliance controls.
• Develop enterprise patterns for embedding AI into business workflows with appropriate risk, security, and ethical controls.
• Design AI telemetry and observability frameworks to monitor model behavior, performance, usage, and risk at scale.
• Define model selection and decision frameworks to guide fit-for-purpose use of AI models based on cost, performance, latency, and risk.
• Evaluate and define architectural approaches for Small Language Models (SLMs) and other emerging AI capabilities.
• Translate enterprise AI strategy into architectural principles, standards, and implementation guidelines.
• Partner with security, risk, data, and engineering teams to ensure AI platform architecture is secure, compliant, and implementable.
• Collaborate with delivery teams and domain leadership to ensure consistent adoption of AI platform standards.
• Provide architectural guidance and recommendations to senior leadership and governance forums.
• Identify opportunities for reuse, optimization, and ROI-driven AI architecture decisions across the enterprise.

Required Qualifications

• Bachelor’s degree and 7+ years of relevant work experience, or in lieu of a degree, a combined minimum of 11 years of higher education and/or relevant work experience.
• 7+ years of experience in software engineering, solution architecture, or enterprise architecture roles.
• Strong experience defining or leading enterprise architecture across application, data, cloud/infrastructure, security, integration, and operations domains.
• Experience developing enterprise architecture roadmaps, target-state architectures, and transition strategies in partnership with domain leadership.
• Experience translating enterprise strategy into architecture principles, standards, patterns, and governance frameworks.
• Strong understanding of AI platforms, AI architecture, or emerging AI technologies (including LLMs and/or Small Language Models).
• Experience designing or guiding enterprise AI governance, guardrails, and model selection frameworks (cost, risk, performance, latency tradeoffs).
• Experience with architecture tools and frameworks (e.g., enterprise architecture modeling, roadmapping, or governance tools).
• Strong ability to engage with senior leadership and executive stakeholders, presenting complex technical concepts clearly and effectively.
• Ability to evaluate emerging technologies and assess enterprise impact, ROI, and scalability.

Preferred Qualifications

• Graduate degree in a technical or business discipline.
• Experience with AI platforms, machine learning systems, or enterprise AI architecture.
• Cloud certification (AWS, Azure, or GCP).
• Experience working in Agile environments.
• Enterprise Architecture certification (TOGAF or equivalent).
• Experience in financial services or other regulated industries.
• Experience working across multiple architecture domains (data, application, infrastructure, security).