Sr Staff AI Engineer

Job Description:

Job Summary: The Sr. Staff AI Engineer is a senior individual contributor responsible for designing and delivering scalable, production ready AI solutions that advance Penn Mutual’s Connected Data Strategy. This role applies deep software and AI engineering expertise to deliver enterprise AI capabilities across LLM based services, retrieval augmented generation (RAG), document intelligence, and cloud native integrations, leveraging AWS native technologies, domain owned data products, and third party SaaS platforms.   

Responsibilities 

AI Engineering:  

• Design, implement, and maintain production AI services using AWS native technologies such as Bedrock, SageMaker, Lambda, EventBridge, OpenSearch, S3, and DynamoDB. 

• Build and operate retrieval augmented generation (RAG) pipelines, including embedding strategies, vector search, prompt orchestration, and response evaluation. 

• Engineer LLM enabled APIs and workflows that integrate directly into enterprise applications and data products. 

• Develop solutions for unstructured data and document intelligence, including extraction, enrichment, classification, and search. 

Quality and Operations: 

• Apply strong software engineering practices including CI/CD, automated testing, infrastructure as code, and runtime observability. 

• Ensure AI systems meet requirements for performance, scalability, security, cost efficiency, and resilience. 

• Partner with platform and operations teams to support production readiness, monitoring, and ongoing optimization of AI workloads. 

• Continuously improve solution quality through experimentation, tuning, and performance analysis. 

Leadership and Collaboration: 

• Collaborate closely with Architecture, Data, Platform, and Product teams to deliver AI solutions aligned with enterprise direction and domain needs. 

• Provide technical leadership through implementation, code reviews, and design guidance for AI related initiatives. 

• Mentor engineers and teams on applied AI engineering patterns, cloud native development, and responsible AI practices. 

• Contribute reusable components, patterns, and reference implementations to accelerate AI adoption across IM&T. 

• Assist Software Engineering leaders with project planning via recommendations on scope, estimates, priority, and dependencies. 

Governance and Compliance: 

• Implement AI solutions that adhere to enterprise governance, security, privacy, and model risk standards. 

• Ensure AI systems are observable, auditable, and well documented to support compliance and operational oversight. 

• Partner with governance and compliance teams to align technical implementations with applicabl