GenAI Architect
Job in
Philadelphia, Philadelphia County, Pennsylvania, 19102, USA
Listed on 2026-09-03
Listing for:
Purple Drive Technologies
Full Time
position Listed on 2026-09-03
Job specializations:
-
IT/Tech
AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist
Job Description & How to Apply Below
Purple Drive
GenAI Architect Share Contractual Philly PDT - 8175
Key
Skills:
- Open AI
- Cloud Infra
- Azure Security
- Gen AI
- LLM
Experience Level 8 Plus years (with at least 2 to 3 years in AI/ML/GenAI)
Key Responsibilities
- Design and implement GenAI architectures leveraging Microsoft Azure and Open AI models
- Lead solution architecture and integration of generative AI models into enterprise applications
- Collaborate with data scientists, engineers, and business stakeholders to define AI use cases and technical strategy
- Develop and optimize prompt engineering, model fine-tuning, and deployment pipelines
- Design scalable data storage and retrieval layers, using vector databases (e.g., Azure AI Search, Pinecone, or FAISS)
- Evaluate third-party GenAI APIs and tools for integration
- Ensure compliance with data security, privacy, and responsible AI guidelines
- Support performance tuning, monitoring, and optimization of AI solutions in production Stay updated with evolving trends in GenAI and Azure offerings, especially related to Open AI
Required Skills and Qualifications
- Proven experience architecting AI/ML or GenAI systems on Azure
- Hands-on experience with Open AI, Azure OpenAI, and related Azure AI tools
- Strong understanding of LLMs, prompt engineering, and text generation frameworks
- Proficiency in PL/SQL with advanced SQL and performance tuning
- Experience with MLOps, CI/CD pipelines, and AI model lifecycle management
- Solid knowledge of Python, APIs, RESTful services, and cloud-native architecture Familiarity with vector databases and semantic search concepts
- Strong communication and stakeholder management skills
Preferred Qualifications
- Azure Cloud certifications
- Experience in model fine-tuning and custom LLM training
- Knowledge of Lang Chain, RAG (Retrieval-Augmented Generation) frameworks
- Exposure to data privacy regulations (GDPR, HIPAA, etc.)
- Background in natural language processing (NLP) and deep learning
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