Cloud Engineer - 8+yrs - Cloud-native SaaS applications, Java, Python, Kafka/Flink/Spark/Ice berg
Data & Analytics Senior Cloud Engineer for Webex Contact Center
Be part of the Cisco Webex Contact Center team, where technology, innovation, and collaboration come together to transform customer experiences. We foster a culture of curiosity, creativity, and continuous learning, empowering team members to experiment, challenge existing approaches, and bring new ideas to life.
As a Data Architect for Webex Contact Center, you will serve as a senior technical leader responsible for defining the architecture, standards, and strategic direction of the data, analytics, and reporting platform. You will design scalable, secure, reliable, and future-ready data architectures that support real-time and historical reporting, customer journey insights, artificial intelligence, machine learning, and other data-driven Contact Center experiences.
Working closely with Product Managers, engineering leaders, you will shape how Contact Center data is collected, processed, modeled, stored, governed, and consumed. Your technical direction will help ensure data accuracy, consistency, security, scalability, and high availability while enabling faster delivery of reporting, analytics, and AI-powered capabilities for Webex Contact Center customers.
Key Responsibilities- Design, develop, and operate AI-ready data platform components that power next-generation intelligent experiences across Webex Contact Center.
- Partner with the Data Platform Architect to build the foundational intelligence layer that transforms enterprise contact center data into predictive insights, recommendations, and autonomous decision-making.
- Develop scalable data pipelines, feature engineering frameworks, and intelligent data services that enable training, deployment, and continuous improvement of custom AI and machine learning models.
- Build reusable AI platform capabilities including feature stores, inference pipelines, semantic search, vector retrieval, embeddings, knowledge augmentation, and model-serving infrastructure.
- Develop high-performance streaming and batch data processing systems capable of handling billions of customer interaction events with low latency and high reliability.
- Build APIs and platform services that expose AI-ready data to Reporting, Analytics, AI Agents, Routing, Workforce Optimisation, and other intelligent platform capabilities.
- Optimize AI and data platform performance across ingestion, feature computation, model inference, storage, retrieval, and serving to meet enterprise-scale latency and throughput requirements.
- Evaluate emerging AI technologies, machine learning frameworks, vector databases, and modern data infrastructure, rapidly prototyping new ideas that can differentiate Webex Contact Center.
- Participate in architecture discussions, design reviews, and technical innovation, contributing to the evolution of Cisco's AI-first data platform.
- Mentor engineers and champion engineering excellence through clean architecture, automation, observability, testing, and knowledge sharing.
- Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, or a related technical field.
- 8+ years of experience building distributed cloud-native SaaS applications.
- Strong software engineering expertise in Java and/or Python with experience developing production-grade backend services.
- Hands-on experience building modern data platforms using technologies such as Kafka, Flink, Spark, Iceberg, Pinot, ClickHouse, or equivalent streaming and analytical systems.
- Good understanding of modern AI and machine learning architectures, including feature engineering, embeddings, vector search, Retrieval-Augmented Generation (RAG), semantic retrieval, inference pipelines, and model-serving frameworks.
- Experience integrating machine learning models into large-scale production systems, with an understanding of model lifecycle, monitoring, evaluation, and continuous improvement.
- Strong understanding of distributed systems, event-driven architectures, microservices, and cloud-native application design.
- Experience building scalable data processing pipelines supporting both real-time and offline AI workloads.
- Experience optimizing large-scale systems for latency, throughput, scalability, reliability, and operational efficiency.
- Hands-on experience with AWS or GCP, Kubernetes, Docker, and cloud-native engineering practices.
- Strong understanding of data modelling, APIs, distributed storage, caching, and performance tuning.
- Excellent analytical, debugging, and problem-solving skills with the ability to work across complex enterprise platforms.
- Experience building AI-powered enterprise platforms where machine learning is a core product capability rather than a standalone service.
- Experience with LLMs, fine-tuning, prompt engineering, agentic workflows, or domain-specific AI applications.
- Experience with vector databases, feature stores, knowledge graphs, semantic indexing, and intelligent retrieval systems.
- Familiarity with modern AI frameworks such as PyTorch, TensorFlow, LangChain, LlamaIndex, MLflow, Ray, or equivalent technologies.
- Experience developing custom AI or machine learning models for recommendation systems, forecasting, anomaly detection, conversational intelligence, or decision optimisation.
- Experience optimizing GPU-accelerated inference, model-serving infrastructure, and large-scale AI workloads.
- Experience working on enterprise SaaS platforms handling large-scale customer data, preferably in Contact Center, Customer Experience, CRM, or communications platforms.
- Strong interest in applying AI to solve complex customer problems and creating differentiated product capabilities beyond commercially available AI models.
#collabhiring
At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.
Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.
We are Cisco, and our power starts with you.
Skills Required
- Bachelor's or Master's degree in Computer Science, Engineering, AI, ML, or related field.
- 8+ years building distributed cloud-native SaaS applications.
- Production-grade backend development experience in Java and/or Python.
- Hands-on experience with Kafka, Flink, Spark, and Iceberg (or equivalent streaming/analytical systems).
- Experience with analytical stores such as Pinot or ClickHouse.
- Strong understanding of modern AI/ML architectures: feature engineering, embeddings, vector search, RAG, inference pipelines.
- Experience integrating machine learning models into large-scale production systems and model lifecycle management.
- Strong knowledge of distributed systems, event-driven architectures, microservices, and cloud-native design.
- Experience building scalable real-time and offline data processing pipelines.
- Experience optimizing systems for latency, throughput, scalability, reliability, and operational efficiency.
- Hands-on experience with AWS or GCP.
- Experience with Kubernetes and Docker and cloud-native engineering practices.
- Strong understanding of data modeling, APIs, distributed storage, caching, and performance tuning.
- Excellent analytical, debugging, and problem-solving skills.
- Experience building AI-powered enterprise platforms, LLMs, fine-tuning, prompt engineering, or agentic workflows.
- Familiarity with PyTorch, TensorFlow, LangChain, LlamaIndex, MLflow, Ray, or equivalent frameworks.
- Experience with vector databases, feature stores, knowledge graphs, semantic indexing, and retrieval systems.
- Experience optimizing GPU-accelerated inference and model-serving infrastructure.
- Experience in Contact Center, Customer Experience, CRM, or communications SaaS platforms.
Cisco Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Cisco and has not been reviewed or approved by Cisco.
-
Healthcare Strength — Health coverage is described as robust with multiple plan options and access to onsite/virtual LifeConnections Health Centers on major campuses. Company materials also highlight mental-health resources and comprehensive preventive care, supporting strong core medical benefits.
-
Leave & Time Off Breadth — Time away includes company‑wide recharge days, a paid birthday, a year‑end shutdown, and paid Critical Time Off for emergencies. Paid volunteer days further expand opportunities to step away and recharge.
-
Parental & Family Support — Policies include a global minimum for paid parental leave for primary caregivers, caregiving concierge services, and on‑site children’s learning centers in select locations. In the U.S., family‑building support is consolidated under Carrot with a defined lifetime maximum, indicating structured assistance across fertility, preservation, adoption, and surrogacy.
Cisco Insights
What We Do
Cisco (NASDAQ: CSCO) enables people to make powerful connections--whether in business, education, philanthropy, or creativity. Cisco hardware, software, and service offerings are used to create the Internet solutions that make networks possible--providing easy access to information anywhere, at any time. Cisco was founded in 1984 by a small group of computer scientists from Stanford University. Since the company's inception, Cisco engineers have been leaders in the development of Internet Protocol (IP)-based networking technologies. Today, with more than 71,000 employees worldwide, this tradition of innovation continues with industry-leading products and solutions in the company's core development areas of routing and switching, as well as in advanced technologies such as home networking, IP telephony, optical networking, security, storage area networking, and wireless technology. In addition to its products, Cisco provides a broad range of service offerings, including technical support and advanced services. Cisco sells its products and services, both directly through its own sales force as well as through its channel partners, to large enterprises, commercial businesses, service providers, and consumers.
