Technical Architect Data, Analytics & AI

Location: Princeton New Jersey Hybrid 40-50% onsite

Role Overview

We are seeking aTechnical 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 intransforming 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 acrossanalysis 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.
• Bachelors or Masters degree in Computer Science Engineering Information Systems Mathematics or Business (or equivalent).
• Strong experience with cloud platforms and services including:
• Azure (e.g.; Azure AI Studio Azure Data Services and tools)
• AWS (e.g.; Amazon Bedrock Sagemaker Data Services and tools)
• Databricks
• Handson experience with enterprise data concepts including:
• Data Intake and Ingestion
• Data Warehousing
• Data Lakes / Lakehouse architectures
• ETL / ELT
• Interactive and operational reporting
• Statistical and regulatory reporting
• Master Data Management (MDM)
• Data Governance Quality Security Audit Balance & Control
• Solid understanding of enterprise architecture practices including:
• Architectural patterns
• Roadmaps
• Architecture Review Boards
• Solution Design Boards
• Experience defining data management and AI roadmaps cloudbased services and reusable architectural patterns.
• Experience integrating operational data with enterprise data lakes.
• Strong understanding of data integration challenges and solution patterns.
• Experience with statistical and data science languages such as Python and R (strong asset).
• Exposure to AI/ML concepts including model development deployment monitoring and MLOps (required).
• Familiarity with Generative AI concepts AI platforms and enterprise adoption considerations (strong asset).
• Strong business acumen with deep understanding of:
• Financial systems
• Corporate and backoffice systems
• Enterprise data management analytics and AI technology landscape
• Strong problemsolving skills unquestioned integrity and high collaboration capability.
• Passion for innovation continuous improvement modernization and change management.
• Excellent written and verbal communication skills with the ability to communicate effectively at all levels.
• High sense of ownership accountability and pride in delivered outcomes.

At Munich Re US we see Diversity and Inclusion as a solution to the challenges and opportunities all around us. Our goal is to foster an inclusive culture and build a workforce that reflects the customers we serve and the communities in which we live and work. We strive to provide a workplace where all of our colleagues feel respected valued and empowered to achieve their very best every day. We recruit and develop talent with a focus on providing our customers the most innovative products and services.

We are an equal opportunity employer. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

The Company is open to considering candidates in Princeton NJ. The salary range posted below applies to the Companys Princeton location.

The base salary range anticipated for this position is$141800 - $207900plus opportunity for company bonus based upon a percentage of eligible addition the company makes available a variety of benefits to employees including health insurance coverage an employee wellness program life and disability insurance 401k match retirement savings plan paid holidays and paid time off (PTO).

The salary estimate displayed represents the typical salary range for candidates hired in this position in Princeton. Factors that may be used to determine your actual salary include your specific skills how many years of experience you have and comparison to other employees already in this role. Most candidates will start in the bottom half of the range.