AI Platform Manager

Key Responsibilities

• Architect Scalable Data & AI Solutions : Design and architect end-to-end data and AI systems, including data pipelines, model workflows, and AI services, ensuring scalability, reliability, and performance across enterprise use cases.
• GenAI Enablement : Help Integrate Generative AI capabilities such as entity extraction, summarization, and retrieval-augmented generation (RAG) into enterprise data platforms to enrich and contextualize data assets.
• Agentic AI Frameworks : Architect autonomous AI agent systems using frameworks like LangGraph, CrewAI, or similar, enabling multi-agent collaboration and orchestration for complex business tasks.
• AI / ML Strategy & Governance : Define and implement AI / ML architecture standards, model lifecycle governance, and responsible AI practices including bias testing, explainability, and ethical deployment.
• Cross-Functional Collaboration : Partner with Data Engineers, MLOps, and Platform teams to ensure seamless integration of AI models into production environments, including containerization, CI / CD pipelines, and monitoring.
• Tooling & Platform Standardization : Drive standardization of AI development tools, libraries, and infrastructure across teams to improve productivity, maintainability, and compliance.
• Advanced Analytics Enablement : Enable teams to build high-performing models by providing architectural guidance on model selection, and performance optimization.
• Data Architecture Alignment : Work closely with data architects to align AI solutions with enterprise data strategy, including data lakehouse design, metadata management, and data quality frameworks.
• Innovation & Thought Leadership : Stay ahead of emerging trends in AI, GenAI, and data architecture;
• evaluate new technologies and frameworks for adoption;

and evangelize best practices across the organization.