28 days ago
Bengaluru, IndiaStaff+
Responsibilities
- Lead domain strategy across demand and supply planning, Integrated Business Planning, manufacturing operations, quality, and inventory management.
- Design end-to-end architectures for AI/LLM applications, Agentic AI workflows, intelligent automation, analytics solutions, and modern data platforms.
- Lead large-scale programs from strategic planning and solution definition through development, deployment, adoption, and optimization.
- Conduct stakeholder workshops, define requirements, develop solution strategies, and build ROI and cost-benefit analyses.
- Define AI-ready data strategies covering governance, quality, standards, integration, and accessibility.
- Explore and implement Agentic AI, RAG, LLMs, fine-tuning, graph analytics, multi-agent workflows, and intelligent automation.
- Translate supply chain transformation strategies into data, AI, and analytics roadmaps.
- Provide technical oversight for enterprise applications, analytical dashboards, data products, and AI 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.
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 Generative AI and LLM application experience, including hands-on production AI deployment.
- 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 involving structured outputs, guardrails, and workflow optimization.
- Understanding of machine learning, statistical modeling, time-series analysis, and optimization techniques.
- Preferred experience includes semiconductor, electronics, manufacturing, supply chain, modern data platforms such as Snowflake, Oracle ERP, MES, APIs, cloud platforms, full-stack technologies, and AI-ready data governance.
- Preferred certifications include Data Science, AI, Cloud, or related disciplines.
Tech Stack
Snowflake
Categories
About Cisco
Cisco designs and sells networking, security, and collaboration platforms for enterprises, service providers, and governments, spanning routers and switches, Wi‑Fi, firewalls, zero‑trust, observability, and cloud-managed IT (Meraki) plus Webex. Its business model mixes hardware, software subscriptions, and support/consulting services. Founded in 1984 and headquartered in San Jose, California, Cisco is a public company traded on Nasdaq and serves customers across data centers, campuses, and service provider networks.