Lead Data Scientist - Architect Gen AI

CapgeminiTampa, FL
3dOnsite

About The Position

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.Onsite Location: Tampa, FLKey Responsibilities: GenAI Adoption Drive the identification evaluation and adoption of emerging Generative AI technologies and tools to develop innovative solutions and enhance existing platforms Actively design develop and implement AIML solutions within financial applications with a strong emphasis on practical GenAI adoption: This includes handson coding prototyping and deploying GenAI solutions. Agentic AI for Business Process Automation: Be part of end to end design prototyping and implementation of Agentic AI solutions focused on automating critical business processes ensuring they address business needs and scale effectively across the enterprise.  This includes designing and implementing Retrieval Augmented Generation RAG systems to enhance accuracy and contextuality especially for financial data. Chatbot Development Design develop and deploy intelligent chatbot solutions capable of interacting with users across both structured data sources eg databases APIs and unstructured data eg documents emails free text leveraging GenAI for natural language understanding and generation in complex conversational flows. Document Processing OCR Integration Implement solutions for processing and extracting information from documents including integrating Optical Character Recognition OCR technologies to handle scanned documents and images making their content available for GenAI models. TexttoSQL Implementation Develop and deploy solutions leveraging Large Language Models to facilitate TexttoSQLcapabilities enabling users to generate SQL queries from natural language requests thus simplifying data access and analysis from structured databases. Data Analysis Feature Engineering Analyze large complex datasets identify intricate patterns and extract actionable insights leveraging GenAI capabilities for data augmentation or synthetic data generation particularly relevant for Agentic AI applications. Data Pipeline Development Build and maintain robust scalable data pipelines for data ingestion processing and transformation specifically optimizing for the unique requirements of GenAI model training and inference. Cross Functional Collaboration Partner with multiple management teams and business stakeholders to deeply understand requirements and translate them into precise technical specifications and actionable roadmaps incorporating GenAI and Agentic AI possibilities into discussions. System Enhancements Architecture Identify and define necessary system enhancements to deploy new GenAI products and process improvements Ensure application design adheres to the overall architecture blueprint integrating GenAI and Agentic AI components seamlessly. Problem Resolution: Resolve a variety of highimpact problems projects through indepth evaluation of complex business processes system processes and industry standards applying GenAI and Agentic AI where they can offer innovative solutions. Tool Technology Evaluation: Evaluate and select appropriate Generative AI tools and technologies including specialized frameworks libraries and cloud AI services eg AWS SageMaker Azure ML Google AI Platform with a focus on GenAI adoption and Agentic AI capabilities Documentation Monitoring: Develop and maintain comprehensive documentation for AIML models and systems specifically addressing GenAI and Agentic AI implementations Manage and monitor the performance efficiency and reliability of deployed AIML models including evaluating the effectiveness of GenAI components in production. Risk Assessment: Appropriately assess risk when business decisions are made demonstrating particular consideration for the firms reputation and safe guarding the client and its clients and assets by driving compliance with applicable laws rules and regulations adhering to Policy applying sound ethical judgment regarding personal behavior conduct and business practices.

Responsibilities

  • GenAI Adoption Drive the identification evaluation and adoption of emerging Generative AI technologies and tools to develop innovative solutions and enhance existing platforms Actively design develop and implement AIML solutions within financial applications with a strong emphasis on practical GenAI adoption: This includes handson coding prototyping and deploying GenAI solutions.
  • Agentic AI for Business Process Automation: Be part of end to end design prototyping and implementation of Agentic AI solutions focused on automating critical business processes ensuring they address business needs and scale effectively across the enterprise.
  • This includes designing and implementing Retrieval Augmented Generation RAG systems to enhance accuracy and contextuality especially for financial data.
  • Chatbot Development Design develop and deploy intelligent chatbot solutions capable of interacting with users across both structured data sources eg databases APIs and unstructured data eg documents emails free text leveraging GenAI for natural language understanding and generation in complex conversational flows.
  • Document Processing OCR Integration Implement solutions for processing and extracting information from documents including integrating Optical Character Recognition OCR technologies to handle scanned documents and images making their content available for GenAI models.
  • TexttoSQL Implementation Develop and deploy solutions leveraging Large Language Models to facilitate TexttoSQLcapabilities enabling users to generate SQL queries from natural language requests thus simplifying data access and analysis from structured databases.
  • Data Analysis Feature Engineering Analyze large complex datasets identify intricate patterns and extract actionable insights leveraging GenAI capabilities for data augmentation or synthetic data generation particularly relevant for Agentic AI applications.
  • Data Pipeline Development Build and maintain robust scalable data pipelines for data ingestion processing and transformation specifically optimizing for the unique requirements of GenAI model training and inference.
  • Cross Functional Collaboration Partner with multiple management teams and business stakeholders to deeply understand requirements and translate them into precise technical specifications and actionable roadmaps incorporating GenAI and Agentic AI possibilities into discussions.
  • System Enhancements Architecture Identify and define necessary system enhancements to deploy new GenAI products and process improvements Ensure application design adheres to the overall architecture blueprint integrating GenAI and Agentic AI components seamlessly.
  • Problem Resolution: Resolve a variety of highimpact problems projects through indepth evaluation of complex business processes system processes and industry standards applying GenAI and Agentic AI where they can offer innovative solutions.
  • Tool Technology Evaluation: Evaluate and select appropriate Generative AI tools and technologies including specialized frameworks libraries and cloud AI services eg AWS SageMaker Azure ML Google AI Platform with a focus on GenAI adoption and Agentic AI capabilities
  • Documentation Monitoring: Develop and maintain comprehensive documentation for AIML models and systems specifically addressing GenAI and Agentic AI implementations Manage and monitor the performance efficiency and reliability of deployed AIML models including evaluating the effectiveness of GenAI components in production.
  • Risk Assessment: Appropriately assess risk when business decisions are made demonstrating particular consideration for the firms reputation and safe guarding the client and its clients and assets by driving compliance with applicable laws rules and regulations adhering to Policy applying sound ethical judgment regarding personal behavior conduct and business practices.

Benefits

  • Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
  • Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
  • Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
  • Life and disability insurance
  • Employee assistance programs
  • Other benefits as provided by local policy and eligibility
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