Data Engineer

Responsibilities

• Design and deploy Generative AI applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and intelligent automation frameworks.
• Define enterprise AI architecture, reference patterns, and best practices to ensure scalable, secure, and responsible AI adoption across the organization.
• Integrate AI capabilities with enterprise applications, data platforms, APIs, and cloud-native services to deliver end-to-end intelligent solutions.
• Drive innovation by evaluating emerging AI technologies, developing proof-of-concepts, and accelerating the transition of successful prototypes into production.
• Collaborate with data engineers, software engineers, and platform teams to build robust AI pipelines, model integration frameworks, and MLOps capabilities.
• Meet and exceed governance, security, and compliance standards for AI solutions, ensuring alignment with enterprise architecture and responsible AI principles.
• Mentor engineering teams on AI solution design, architecture best practices, and modern AI development frameworks to elevate organizational AI capabilities.
• Measure and communicate the business impact of AI initiatives through improved productivity, operational efficiency, automation, and enhanced customer experiences.

Requirements

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related technical field.
• 10+ years of experience in software engineering, solution architecture, data engineering, or enterprise application development, including at least 3 years delivering AI or Machine Learning solutions.
• Hands-on experience designing and deploying Generative AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, prompt engineering, and AI orchestration frameworks.
• Strong proficiency in Python and experience with cloud platforms such as AWS, Azure, or Google Cloud, including AI/ML services and modern data platforms.
• Experience architecting scalable enterprise solutions using APIs, microservices, cloud-native architectures, and modern DevOps/MLOps practices.
• Experience implementing Agentic AI, AI copilots, intelligent automation, or enterprise knowledge assistants using frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar technologies.
• Knowledge of enterprise data platforms including Snowflake, Databricks, dbt, Spark, vector databases, and data governance frameworks.
• Strong understanding of Responsible AI principles, AI security, governance, model evaluation, and compliance considerations.
• Excellent communication and stakeholder management skills with the ability to influence technical and business leaders across cross-functional organizations.
• Demonstrated passion for innovation, continuous learning, mentoring engineering teams, and driving enterprise AI adoption from proof of concept to production.
• Why Cisco?
• We are Cisco, and our power starts with you.
• At Cisco,

Additional Information

Meet the Team Join a high-performing team that is transforming the way Cisco delivers enterprise data, analytics, and AI-driven business solutions. Our organization builds next-generation platforms that power critical business capabilities across Sales, Customer Success, Services, Renewals, and Enterprise Agreements. We are at the forefront of leveraging Generative AI, Agentic AI, Machine Learning, and modern cloud technologies to automate complex workflows, accelerate engineering productivity, and deliver intelligent business insights at scale. As part of this team, you will shape Cisco's AI strategy by designing innovative solutions that solve real business challenges while influencing enterprise-wide technology adoption.

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