Amazon Web Services (AWS), Application Programming Interface (API), Artificial Intelligence (AI), Cloud Computing, Conversation Engine, Cross-Functional, DevOps, Enterprise Protection, Java, Metadata, Microservices, Microsoft SharePoint, Microsoft Windows Azure, Node.js, Python Programming/Scripting Language, Search Technology, Shallow Parsing, Technical/Engineering Design, Use Cases, User Documentation
Role: Principal Engineer -Technology Architect - Generative AI
Experience: 13 - 15 Years
Location: Exton, PA
Arrangements- Hybrid 3 days office - Exton, Pennsylvania
Rounds of interviews: 2 internal + 1 client round
Rate: : $94-$100/hr. c2c all inclusive
Client: Ricoh (Please don't share this with candidates)
Job Description :
Key Responsibilities :
• Lead architecture and technical design for GenAI solutions across the enterprise
• Build cloud native systems using Azure, AWS, Kubernetes/AKS/EKS, containers, and microservices patterns.
• Architect and guide development of LLM/RAG pipelines, embeddings, vector/hybrid search, and metadata processing.
• Support delivery of GenAI enabled applications.
• Partner with cross functional teams to align on architecture, integration patterns, and standards.
• Provide hands on oversight across DevOps, APIs, connectors, and pipeline execution.
• Ensure designs meet enterprise security, governance, and operational requirements.
Required Experience :
• 10+ years in solution architecture and full stack engineering.
• Strong hands on experience with Azure and/or AWS cloud services.
• Expertise in containers, Kubernetes, and cloud-native application patterns.
• Practical experience designing Generative AI solutions using LLMs, RAG, embeddings, chunking, and search technologies.
• Proficiency in Python, Node.js, or Java, API development, and event-driven architectures.
• Familiarity with integrations like SharePoint/Blob connectors, Azure Search, metadata pipelines, and enterprise systems.
Preferred :
• Experience delivering enterprise AI chatbots and multi use case GenAI platforms.
• Knowledge of AI governance, security, and responsible AI practices.