Location: Princeton, New Jersey Hybrid 40-50% onsite
Role Overview
We are seeking a Technical Architect (TA) with deep expertise in Data, Analytics, and Artificial Intelligence (AI) to join the IT Enterprise Architecture organization. This role is accountable for proactively leading data, analytics, and AIdriven technology transformation initiatives and enabling measurable business outcomes across the enterprise.
The Technical Architect will play a critical role in transforming local, legacy, datadriven processes, and systems into centralized, scalable, and groupwide platforms, while ensuring alignment with enterprise architecture standards and business strategy.
Technical Architects provide technical leadership across analysis, design, facilitation, and execution, supporting the evolution of enterprise Data, Analytics, and AI capabilities and the associated application portfolios and technology stacks. The role owns the creation of key architectural deliverables such as targetstate architectures, transformation roadmaps, standards, and guidelines to enable successful project delivery and longterm strategic outcomes.
This position is based in the USA and ensures that Data, Analytics, and AI architecture vision, principles, and standards are consistently executed through a common enterprise framework, with a strong emphasis on cloudbased data platforms, AI enablement, and data governance.
The ideal candidate will help advance organizational directives around simplification, modernization, and innovation by providing architectural leadership in enterprise data platforms, integration components, and AIenabled data strategies.
Key Responsibilities
- Assist in the development of a multiyear Data, Analytics, and AI roadmap, aligned with the Munich Re Target Architecture and Roadmap Development Process, in collaboration with Data & Analytics Enterprise Architects.
- Drive standardization of Data, Analytics, and AI technology standards, principles, and guidelines across multiple business entities.
- Define and maintain technical standards for enterprise data management, analytics platforms, and AI enablement capabilities.
- Design and guide datacentric and AIenabled initiatives, supporting the transition from traditional data architectures to nextgeneration cloud, analytics, and AI platforms.
- Act as an evangelist and ambassador for enterprise architecture standards including Data Governance. Data Intake and Ingestion. Data Modeling, Data Integration, Analytics and AI lifecycle management
- Collaborate closely with Business Solutions teams, Technology Architects, and Enterprise Data Architects across initiatives and implementations.
- Identify technologyrelated business pain points by mapping business capabilities to current platforms, leveraging EA practices and participating in innovation activities, including AI adoption.
- Enable IT development and infrastructure teams to make informed technology decisions through frameworks, reference architectures, standards, and reusable patterns.
- Identify technical risks, architectural gaps, and vulnerabilities that could impact project delivery or lead to postrelease defects.
- Reduce cost and complexity through standardization, reuse, and rationalization of data, analytics, and AI platforms.
- Partner with EA and TA peers (enterprise, solution, and business architects) to derive the futurestate technology architecture, aligned to business strategy and external trends.
- Define migration and transformation plans to close gaps between current and target states, in alignment with Business Solutions and Business Technology Architects.
- Support governance, assurance, and compliance activities to ensure alignment with enterprise architecture standards and policies.
- Assess and articulate the organizational, skills, process, and financial impact of changes to the application portfolio, data platforms, and AI stack.
- Define and govern enterprise AI architecture standards, including model lifecycle management, MLOps, and AI platform integration.
- Ensure responsible and compliant AI adoption, aligned with AI governance, model risk management, data privacy, and security controls.
- Guide the integration of AI/ML capabilities into analytics platforms, including predictive, prescriptive, and generative AI use cases.
- Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions.
- Establish architectural patterns for AI model deployment, monitoring, versioning, and retraining in cloud environments.
- Evaluate emerging AI technologies, tools, and platforms and provide strategic recommendations for enterprise adoption.
Your Profile
- 4+ years of experience in Enterprise Architecture or Technical Architecture.
- Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, Mathematics, or Business (or equivalent).
- Strong experience with cloud platforms and services, including:
- Azure