Generative AI Architect

at  Capgemini

REQUIRED SKILLS:

• 10+ years professional work experience as a data scientist or on advanced analytics / statistics projects with 5+ years’ experience in one of the following sectors: Aerospace & Defense, Automotive, Banking, Consumer Products & Retail, Financial Services, Healthcare, High Tech, Industrial Products, Insurance, Life Sciences, Manufacturing, Public Sector, Telecom, Media & Entertainment, and Energy & Utilities.
• Experienced in design, development, delivery of GenAI solutions with all necessary underlying components and integration within broader IT environments.
• Master’s degree or PhD in Computer Science, Statistics, Economics, Mathematics, or other closely related field
• Proven experience in architecting and designing complex AI/ML systems, with a focus on generative AI technologies. Experience in Gen AI ,natural language processing (NLP) and text generation is a plus.
• Understanding of AI and GenAI domains, GenAI embeddings, and theoretical aspects.
• Work with RAG, vector stores, and semantic search.
• Experience with multimodal models.
• Strong proficiency in machine learning frameworks, libraries, and methodologies such as GPT, GANs, TensorFlow, PyTorch, or similar. Experience with deep learning architectures and techniques.
• Familiarity with software architecture principles, design patterns, and system integration. Familiarity with cloud computing platforms and hyperscaler technologies (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes).
• Excellent problem-solving skills and analytical thinking. Ability to analyze complex problems, propose innovative solutions, and evaluate trade-offs.
• Strong communication and leadership skills. Ability to effectively communicate technical concepts to clients and non-technical stakeholders and lead cross-functional teams.
• Highly Preferred: 5+ years professional experience as and Data and AI thought leader in a large technology consulting firm.

• Solution Design: Collaborate with clients and internal teams to understand business requirements, challenges, and opportunities. Lead the end-end tech stack assessment, architecture design for generative AI solutions (including system components, data pipelines, and deployment strategies), and integration of GenAI solution components into broader IT systems and corresponding architecture.
• Architecture Development: Develop high-level and detailed solution architectures for AI projects. Consider factors such as data integration, solution deployment, scalability, security, performance optimization, and ongoing sustainability.
• Technical Expertise: Serve as the domain expert on AI technologies, including machine learning, natural language processing, computer vision, and other relevant domains. Hands-on development and delivery of GenAI solutions.
• Model Selection: Evaluate and select appropriate generative AI components and algorithms based on project objectives, data characteristics, and performance requirements. Design custom models or adapt existing models to meet specific use cases. Guide the development of vector stores, prompt engineering, performance monitoring based on solution design requirements.
• Governance and Compliance: Define governance frameworks and guardrails for the ethical and responsible use of generative AI technologies.
• Ensure compliance with regulatory requirements and industry and company standards.
• Pre-Sales Support: Assist the sales team in pre-sales activities by providing technical expertise, participating in client meetings, and contributing to proposal development. Translate client requirements into feasible AI solutions.