The AutoQuote team at Cisco builds and operates the automated quoting platform that powers Cisco's global renewals business. Our mission is to generate accurate, ready-to-order quotes at scale — minimizing manual effort for partners and distributors, reducing booking friction, and driving simplification across Cisco's renewal workflows.

We are a product engineering team running a homegrown, cloud-native application hosted on GCP. Our stack is built on a microservices architecture orchestrated with Kubernetes, with Prefect managing our data and workflow pipelines, and Pub/Sub and REST APIs handling communication across services. We move fast, operate at scale, and are actively integrating AI capabilities into the core of what we build.

Your Impact:

We are seeking a skilled Data Science Analyst to join the AutoQuote team at Cisco. This mid-level engineering role focuses on building, maintaining, and improving the software features, data pipelines, and AI-powered capabilities that drive the AutoQuote platform. The ideal candidate is a proficient software engineer who can work independently on moderately complex features, collaborate effectively across the team, and leverage AI tools as a natural part of their development workflow.

AI fluency is a core requirement — candidates should be comfortable using LLMs, AI coding assistants, and prompt engineering techniques as everyday tools to accelerate development and improve code quality.

What You'll Do:

• Design and implement software features and enhancements within the AutoQuote application, working across backend services, data pipelines, and service integrations.

• Build and maintain data processing workflows using Prefect, GCP services, and REST APIs within a cloud-native microservices architecture.

• Write clean, well-tested code that adheres to team standards and passes CI/CD quality gates — Python proficiency is expected, with the ability to apply other languages as the problem requires.

• Actively use AI tools — including LLMs (Claude, Gemini, GPT) and AI coding assistants — to accelerate development, generate and validate code, and solve complex engineering problems.

• Participate in architecture and design reviews, contributing well-reasoned technical analysis and recommendations.

• Collaborate with senior engineers, product management, and QA to translate requirements into robust, testable implementations.

• Lead code reviews for junior engineers and provide constructive technical feedback.

• Investigate and resolve production bugs; contribute to improving system reliability and operational health.

• Stay current on AI frameworks, cloud-native tooling, and engineering best practices.

Minimum Qualifications:

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.

• 3–5 years of professional software engineering experience, with demonstrated ability to work independently on moderately complex features.

• Strong proficiency in Python; working knowledge of additional languages or frameworks appropriate to the task at hand.

• Experience building and maintaining data pipelines using workflow orchestration tools (Prefect, Airflow, or equivalent) and cloud data services.

• Hands-on experience with GCP and/or AWS, including cloud storage, serverless functions, and managed services.

• Demonstrated ability to use AI tools — such as Claude, ChatGPT, or Gemini — to accelerate development, debug problems, and produce higher-quality code faster.

• Solid understanding of software testing practices, CI/CD pipelines, and agile development methodologies.

• Working knowledge of containerization (Docker) and familiarity with Kubernetes or equivalent orchestration platforms.

• Good communication skills; comfortable collaborating across engineering and cross-functional teams.

Preferred Qualifications:

• Experience with microservices architecture and REST API development at scale.

• Familiarity with AI/ML frameworks or cloud-managed AI services (e.g., GCP Vertex AI, AWS Bedrock, LangChain).

• Exposure to prompt engineering, LLM integration, or agentic workflow design.

• Prior experience in an enterprise product engineering environment.

ADDITIONAL INFORMATION

• This role expects an engineer who can take on features with moderate guidance and steadily grow toward greater independence and broader platform ownership.

• AI-assisted development is a standard expectation — candidates should bring demonstrated comfort with AI tools as everyday development instruments.

• The candidate will collaborate with both senior engineers and junior teammates and should be effective operating in both directions.

• All work is conducted in adherence to Cisco security and compliance requirements; responsible handling of program data and AI-generated output is essential.

Why Cisco? 

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.