What are the responsibilities and job description for the GEN AI Architect position at Virtusa?
Title: GenAI Architect
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 LangChain, RAG (Retrieval-Augmented Generation) frameworks
Exposure to data privacy regulations (GDPR, HIPAA, etc.)
Background in natural language processing (NLP) and deep learning
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 LangChain, RAG (Retrieval-Augmented Generation) frameworks
Exposure to data privacy regulations (GDPR, HIPAA, etc.)
Background in natural language processing (NLP) and deep learning