Minimum Qualifications/Requirements:- Bachelor’s degree in related field (e.g., Computer Science, Computer Engineering, Information Technology, System Analysis, etc.) or equivalent combination of education and work experience
- Typically, 8+ years of experience in IT and business/industry including architecture experience (design, development, deployment, road-mapping), systems life cycle management, and infrastructure planning and operations
- Experience in working in multiple, diverse technologies and processing environments.
- Native-level proficiency/fluent in English
- Experience in DevOps and Agile technology environments (preferred)
What you will do:
As the Sr. Principal Integrations Solution Architect, you will…
· Design AI-enabled integration solutions across a portfolio that address significant business problems and deliver measurable value.
· Evolve and maintain conceptual and high-level architecture for integration-related initiatives, ensuring consistency with enterprise and domain-level guiding principles and business objectives.
· Ensure solutions meet broad non-functional requirements, including resiliency, availability, maintainability, upgradeability, and scalability.
· Shepherd the detail design ensuring the detail design aligns with the high-level design and architecture direction.
· Communicate architectural approach to stakeholders, translating technical concepts for business and cross-functional understanding.
Who you are:
· Strong leadership in solution architecture and strategic delivery, from vision through execution, including cross-functional team management and stakeholder communication.
· Strong knowledge of system development life cycle (SDLC) methodologies, including waterfall, agile, SAFe, DevOps, and others.
· Strong technical expertise across modern IT ecosystems, such as SaaS, IaaS, PaaS, SOA, APIs, microservices, event-driven, batch, and streaming.
· Proficient in integration and cloud platforms, including MuleSoft, Informatica, Google Cloud Platform, and Azure.
· Demonstrated experience enabling AI/ML or GenAI solutions through integration architecture (APIs, events/streams, data pipelines, and platform integrations).
· Working knowledge of Responsible AI considerations (data privacy, security, access controls, model risk, auditability) as they impact integration design.
· Strong skills in translating business needs into technical solutions and mentoring team members through knowledge sharing and collaboration
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