Senior Architect - Enterprise AI HLD Architect

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• →Works across the business, operations and technology to create the solution intent and architectural vision for complex solutions and prioritize functional and non-functional requirements into a technology backlog to enable the technology roadmap and functionality to support evolving capabilities and services
• →Contributes to the creation of the architecture roadmap of defined domains (Business, Application, Data, and Technology) in support of the product roadmap and the development of best practices including standardized templates
• →Clarifies the architecture, assists with system design to support implementation, and provides solution options to resolve any architectural impediments
• →Facilitates solution driven discussions, leads the design of complex architectures, and finds creative solutions through knowledge of domain, practical experiments, and proof of concepts while ensuring architecture is flexible, modular, and adaptable
• →Educates team members on the technology practices, standardization strategies, and best practices to create innovative solutions
• →Supports the team as needed to select the technology stack required for solutions and helps select preferred technology products
• →Performs design and code reviews to ensure all non-functional requirements are sufficiently met (for example, security, performance, maintainability, scalability, usability, and reliability)
• →Improve the experience for our developers, making it easier to deliver industry-leading solutions, while managing work efficiently and with the right controls
• →Advance our technology platforms through innovation
• →Reduce risk and improve quality across our technology portfolio by aligning to a single enterprise architecture strategy and delivering governance that enables consistency, integration and automation

• 10+ years of engineering and architecture experience with strong technical leadership across enterprise software platforms, developer tooling, or AI-enabled systems
• Demonstrated ownership of architecture design, reference patterns, and technical standards for shared capabilities used across multiple teams or lines of business
• Experience engineering solutions in highly regulated environments with strong SDLC, risk, audit, and control requirements
• Ability to influence architects, engineering teams, and risk partners through clear high-level design guidance, reference architecture, and pragmatic technical standards

• Advanced degree in a technical discipline or equivalent record of senior architecture leadership in enterprise platforms, AI systems design, software delivery architecture, or cloud engineering.

• Deep expertise in platform architecture and enterprise solution design, with the ability to define high-level structures, capability boundaries, and reference patterns for AI-enabled delivery systems
• Strong command of enterprise systems thinking, including tradeoff analysis, dependency management, cross-platform design, and alignment of architecture decisions to long-term enterprise outcomes
• Proven ability to design AI systems architecture that aligns application, data, model, workflow, and platform considerations into coherent and supportable enterprise solutions
• Experience designing architecture patterns that improve developer workflow integration across source control, CI/CD, testing, infrastructure, and AI-enabled delivery services
• Hands-on knowledge of cloud and platform engineering principles required to ensure architecture patterns are practical, scalable, and aligned to enterprise operating models

• Experience applying security and governance by design principles to enterprise AI architecture, including control points, policy alignment, risk-aware patterns, and support for regulated delivery environments
• Strong understanding of architecture decisions that support resiliency, observability, supportability, and operational readiness across AI-enabled delivery systems
• Proven ability to embed a resilience and operability mindset into high-level design through architecture patterns for failure handling, service dependencies, recovery, and sustainable operations

• Hands-on collaboration with platform engineering, security, data, and delivery teams to define integration and interoperability design patterns that connect AI capabilities with enterprise systems, controls, and delivery processes
• Strong foundation in interface design, service interaction patterns, data flow architecture, and platform interoperability required to enable scalable enterprise AI adoption
• Experience shaping reference architectures that balance reuse, flexibility, standardization, and integration complexity across diverse enterprise delivery environments
• Familiarity with architecture review processes, dependency mapping, and cross-domain design alignment needed to make enterprise AI solutions interoperable, governed, and supportable

• Ability to define reference patterns, architecture guardrails, and enablement approaches that improve delivery consistency, design quality, and speed to value across engineering teams
• Proven track record guiding architecture capabilities from concept to enterprise adoption through measurable improvements in solution quality, standardization, governance, and developer alignment
• Demonstrated success connecting architecture investments to delivery acceleration, operational resilience, integration consistency, and reduced complexity across software delivery workflows
• Experience evaluating solution approaches, architectural tradeoffs, and enterprise constraints to guide teams toward scalable, supportable, and high-value AI use cases

• Bachelor’s degree in Computer Science, Engineering, Information Systems, Applied Mathematics, or a related technical field

• Analytical Thinking
• Architecture
• Result Orientation
• Solution Design
• Technical Strategy Development
• Application Development
• Collaboration
• Data Management
• DevOps Practices
• Risk Management
• Agile Practices
• Automation
• Influence
• Solution Delivery Process
• Test Engineering