Dear Candidates,
Role Objective
Season AI Architect is responsible for detail designing conceptual architecture, reference frameworks, to helps accelerate, is future perfect, is scalable, renders agility to accommodate changes. S/he also works closely with client architects and help with review and governance.
Key Responsibilities
- Enterprise AI Architecture execution roadmap
- Designing, developing, deploying and manage advanced AI solutions
- Comprehensive focus on the full end-to-end cycle—from requirements analysis, data understanding and system design to implementation, testing, and integration.
- Designing and overseeing the development of advanced Agentic AI, AI and machine learning solutions.
- This role involves collaborating with cross-functional teams to define system requirements, create scalable architectures, and ensure robust integration of multi-modal data sources. You will provide technical leadership throughout the project lifecycle, from conceptualization to deployment, ensuring each solution aligns with business objectives and industry best practices.
- Candidates will also be expected to utilize Multi-Modal Conversational Platforms and emerging technologies in the GenAI landscape, such as robust evaluation frameworks including RAGas.
Primary Skills:
- Advanced proficiency in AI/ML solution architecture including Agentic Architecture; agentic RAG pipelines; multi-modal data integration (text, image, audio, different languages);
- The role emphasizes expertise in agentic RAG (Retrieval-Augmented Generation) systems, leveraging the latest GenAI capabilities offered by Azure, AWS, Google etc. Expertise in identifying tools and technologies and able to provide comparative recommendations.
- GenAI technologies (Azure OpenAI, Amazon Bedrock, Google Vertex AI, Anthropic, Falcon etc); MCP deployment
- Comprehensive understanding of retail business processes, AI ethics, data privacy, regulatory compliance, agentic RAG, MCP design and deployment, GenAI model implementation on Azure, AWS, Google Cloud, and expertise in Classification, Response Generation, Summarization, Comparison, and Reconciliation tasks across multi-modal datasets.
- Ideal candidates will demonstrate expert analytical and problem-solving skills, mastery of agentic RAG and multi-modal data integration, and experience delivering AI solutions in Classification, Response Generation, Summarization, Comparison, and Reconciliation for retail clients. The position offers a unique opportunity to drive digital transformation and innovation using state-of-the-art agentic RAG, MCP, and GenAI technologies spanning all major cloud platforms. Environments deployment, version control
- Good Understanding of Prompt & AI Engineering concepts
- Demonstrated technical architectural leadership & stakeholder engagement
Secondary Skills:
- Expertise in Python, R, NLP, computer vision, MLOps, API integration; specialty in Classification, Response Generation, Summarization, Comparison, Reconciliation, conversational AI; MCP configuration; UI/UX know-how
Relevant Technologies:
- Practical experience with TensorFlow, PyTorch, Scikit-learn, Docker, Kubernetes, RESTful APIs; GenAI platforms (Azure OpenAI Service, Amazon Bedrock, Google Vertex AI/Generative AI Studio); agentic RAG workflows; multi-modal conversational platforms; evaluation frameworks such as RAGas.
Experience:
- Minimum 8 years in AI/ML development, with at least 3 years in architectural or lead roles, preferably within the retail sector and one project experience in Agentic AI.
Location: India
