Agentic AI Technical Architect at Capgemini | Jobyssey

Key Responsibilities

Lead the development and implementation of enterprise-wide ML and Gen AI/Agentic architectures, ensuring they are scalable, secure, and aligned with business goal.
Proven experience in developing solution across IFAO/IPO/ICO/ISCO Business Services
Lead the end-to-end development & deployment of Gen AI/Agentic initiatives, from ideation and PoC to deployment and scaling.
Identify opportunities for innovation and lead the creation of reusable Gen AI/Agentic assets, accelerators, and frameworks.
Oversee the seamless deployment of Gen AI/Agentic models across platforms, ensuring operational efficiency and compliance.
Develop and implement strategies for continuous integration and delivery of AI solutions, optimizing for performance and maintainability.
Establish and enforce governance policies, standards, and best practices for AI architecture and deployment, ensuring adherence to data privacy and ethical guidelines.
Mentor and lead a technical team and architects fostering a culture of innovation and excellence.
Collaborate with business stakeholders to translate requirements into scalable AI solutions and drive adoption.
Act as the central point of coordination among business lines, technology teams, and clients to ensure consistent delivery outcomes.
Identify opportunities for innovation within the AI domain, focusing on the development of reusable assets and tools.

Qualifications and Skills

Master’s degree in Computer Science, Engineering, Data Science, or a related field. Ph.D. is a plus.
18+ years of experience in enterprise architecture, solution delivery with a strong focus on ML and Gen AI technologies.
Proven experience in solutioning AI-powered solutions at scale, preferably in client-facing environments.
Deep understanding of Gen AI/Agentic frameworks including frameworks like Lang chain and other LLM based services including OpenAI, cloud platforms (AWS, Azure, GCP), and MLOps practices.
Strong understanding of CI/CD, containerization (Docker, Kubernetes), and microservices architecture. Familiarity with Agile and DevOps methodologies.
Excellent communication, stakeholder engagement, and team leadership skill.
Exposure to industry-specific Gen AI/Agentic use cases (e.g., SAP, Salesforce, Finance, Supply Chain etc.,)
Minimum 8 years of extensive experience in solutioning end to end product/assets by leveraging multiple technology components including AI/ML and Generative AI.
Strong problem-solving, strategic thinking and analytical skills, with the ability to synthesize complex information and make data-driven decisions.
Proven experience in leading large-scale AI solution deployments and managing cross-functional teams.