Description
Job Summary
As a Senior Solution Architect / Delivery Manager within the Component Central Operations (CCO) Data & Analytics team at Cisco, you will lead the end-to-end design and delivery of AI-powered solutions that address complex supply chain challenges across Cisco's component ecosystem.
Key Responsibilities
- Provide domain leadership across Demand and Supply Planning, Integrated Business Planning (IBP), Manufacturing Operations, Quality, and Inventory Management, identifying opportunities to improve business performance through technology and data.
- Design end-to-end architectures for AI/LLM-powered applications, Agentic AI workflows, intelligent automation, analytics solutions, and modern data platforms.
- Lead large-scale programs from strategy and solution definition through development, deployment, adoption, and optimization.
- Partner with business and technology stakeholders to conduct workshops, define requirements, develop solution strategies, and build business cases with clear ROI and cost-benefit analysis.
- Define and drive AI-ready data strategies, including data governance, quality, standards, integration, and accessibility.
- Explore and implement emerging AI capabilities including Agentic AI, RAG, LLMs, fine-tuning, graph analytics, multi-agent workflows, and intelligent automation.
- Translate supply chain transformation strategies into actionable data, AI, and analytics roadmaps.
- Provide technical oversight for enterprise applications, analytical dashboards, data products, and AI solutions.
- Partner with IT, engineering, enterprise architects, and cross-functional teams to ensure scalable and sustainable technology solutions.
- Lead testing, deployment, change management, adoption, and post-implementation optimization.
- Mentor teams and promote technical excellence, reusable solutions, responsible AI, model governance, and reproducibility.
- Ensure AI solutions align with enterprise standards for ethics, security, bias mitigation, transparency, and responsible AI.
Requirements
- Master's or PhD in Data Science, Computer Science, Engineering, Information Systems, or a related quantitative field.
- 10+ years of experience in enterprise application development, solution architecture, technology delivery, or program management.
- 8+ years of experience leading large-scale data science, analytics, AI, or digital transformation programs.
- Demonstrated experience leading complex programs and cross-functional technical teams.
- Strong experience with Generative AI and LLM-powered applications.
- Hands-on experience building or deploying AI solutions in production environments.
- Strong understanding of Agentic AI, autonomous workflows, tool calling, and multi-agent orchestration.
- Experience with RAG, embeddings, vector databases, semantic retrieval, reranking, and AI evaluation.
- Strong prompt engineering skills, including structured outputs, guardrails, and workflow optimization.
- Strong understanding of machine learning, statistical modeling, time-series analysis, and optimization techniques.
Nice to Have
- Experience in semiconductor, electronics, manufacturing, or supply chain environments.
- Deep understanding of Demand/Supply Planning, IBP, Manufacturing Operations, Quality, and Inventory Management.
- Hands-on experience with MCP, A2A, Agentic AI frameworks, RAG, LLM fine-tuning, and AI evaluation frameworks.
- Experience designing modern data platforms and data warehouses such as Snowflake.
- Experience integrating data from Oracle ERP, MES, and other enterprise systems.
- Experience with enterprise application development, APIs, cloud platforms, and full-stack technologies.
- Experience defining and implementing AI-ready data governance and data quality frameworks.
- Proven experience leading large transformation programs and driving technology adoption.
- Strong business acumen with the ability to translate complex technical concepts into measurable business outcomes.
- Additional certifications in Data Science, AI, Cloud, or related disciplines are preferred.