AI Architect

Key Responsibilities: – 

  •  Design and Implement Artificial Intelligence and Data Science solutions on Cloud at enterprise scale. 
  •  Contextual understanding of customer requirements with visions, strategies, and roadmaps for implementation. 
  •  Collaboration with solution architect, business analysts and partner architects/stakeholders in Global Delivery model for AI Solution development 
  •  Play a key role in defining the AI architecture and selecting appropriate technologies from a pool of open-source and commercial offerings. Select cloud, on-premises or hybrid deployment models, and ensure new tools are well-integrated with existing data management and analytics tools. 
  •  Audit AI tools and practices across data, models and software engineering with a focus on continuous improvement 

 Technical Qualifications : 

  • Understand the workflow and pipeline architectures of ML and deep learning workloads 
  • .Data science and advanced analytics, including knowledge of advanced analytics tools (such as SAS, R and Python) along with applied mathematics, ML and Deep Learning frameworks (such as TensorFlow) and ML techniques (such as random forest and neural networks). 
  • Hands-on programming skill on at least one language – C#.net or node.js or python. 
  • Expert on Cloud competencies on “Artificial Intelligence” and “Machine Learning” PaaS components:·  
  • Contextual Conversation design (Azure BOT service/Amazon Lex/ Google Dialog flow) – for personalized and humanized interaction with end user for complex business cases·  
  • Natural Language Processing model design, training and publishing for multiple languages· Emotion and Sentiment Analytics· 
  •  Custom Speech model – Speech-to-text and Voice synthesis calibrated for language, accent, pitch, tone, noise and business vocabs.· Computer vision – OCR, Face Recognition, Custom model for Object detection and classifications·  
  • Document/Form Entity Extraction· Cognitive Search on heterogeneous unstructured data· Enterprise Channel Integration for AI · 
  •  Deployment and publish for AI and ML services with ACR, ACI, Docker, Azure Kubernetes· Azure/ AWS/ GCP/ Watson certifications on AI & Data Science like AI 102, DP 100.· 
  •  Enterprise cloud Data repository –Cloud Storage, NoSQL DB, Graph DB, Data Lake· Data Ingestion, Transformation, Analytics – Real-time and batches·  
  • Enterprise Security for AI/ML – Active Directory – Authentication, Authorization· Web app and services – Micro services, Azure functions, Logic apps, API management- Ability to compare and contrast across technologies in any layer objectively with evaluation criteria and considerations 
  •  Excellent communication skills, preparing PowerPoint presentations, executive readouts 

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