Provide thought leadership and guidance to various stakeholders within the business and IT with respect to AI and AI related initiatives including recommendations for adoption, implementation, tooling, and technology transformation.
Architect scalable AI solutions aligned with Penn’s Connected Data Strategy as defined by the head of architecture and CTO.
Assist Head of Architecture with project planning via recommendations on scope, estimates, priority, and dependencies.
Build enterprise AI reference architectures and reusable patterns using best practices and that can be followed by application development teams.
Guide teams in Integrating AI capabilities into AWS-native Lakehouse architecture as well as standing up RAG, Document Intelligence, conversational AI, and agentic automation where appropriate.
Collaborate with compliance and governance teams on applicable standards and policies pertaining to AI solutions, ensuring all deliverables are observable and adhere to those policies.
Establish standards, processes, and best practices to ensure the reliability, security, and scalability of AI based solutions.
Work closely with other departments, such as product management, IT operations, and business stakeholders, to understand requirements and deliver solutions that meet business needs.
Mentor as well as present guidance where needed in the IM&T department with respect to AI industry trends, challenges, risk management, and solution implementation improvements.
Support the head of architecture with evaluating third-party vendors and service providers that provide AI or AI adjacent capabilities.

Requirements

Bachelor’s or master’s degree in computer science, Engineering, or related field.
Advanced degree or relevant certifications (e.g., TOGAF, AWS Certified Solutions Architect) preferred.
10+ years of experience in software architecture, enterprise architecture, and technical leadership roles.
Deep technical expertise in software architecture, cloud computing, microservices, API design, data architecture, and other relevant domains.
Proven track record of defining and implementing architectural guidance that drive business value and innovative solutions utilizing AI technologies.
3–5+ years in AI/ML engineering, data engineering, or enterprise architecture.
2–3+ years architecting AI/ML systems on AWS (e.g. Bedrock, SageMaker, Kendra, Lambda, S3, DynamoDB, EventBridge, OpenSearch).
Hands-on experience designing RAG pipelines, vector retrieval, model orchestration, and LLM‑based services.
Expertise in cloud-native/serverless integration patterns.
Strong understanding of governance, metadata, catalogs, lineage, and access controls.
Experience with unstructured data and document intelligence.
Knowledge of Data Mesh, MLOps/DataOps, and IaC.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

software architecturecloud computingmicroservicesAPI designdata architectureAI/ML engineeringdata engineeringRAG pipelinesmodel orchestrationLLM-based services

Soft Skills

thought leadershipguidancementoringcollaborationproject planningrisk managementcommunicationstakeholder engagementproblem-solvinginnovation

Certifications

TOGAFAWS Certified Solutions Architect