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 Data Science Analysis Manager with deep AI fluency to join the AutoQuote team at Cisco. This role is central to driving the architecture, development, and delivery of AI-powered software features within the AutoQuote application. The ideal candidate brings a strong engineering foundation, hands-on experience integrating and using AI tools within production software, and the ability to guide technical initiatives while mentoring the engineers around them.
AI fluency is a core requirement of this role — not just familiarity, but the demonstrated ability to use LLMs, AI coding assistants, and prompt engineering techniques as everyday development tools to accelerate velocity and improve output quality.
What You'll Do:
Lead the design, development, and integration of AI-powered features, agentic workflows, and automation into the AutoQuote application — using available AI services and tools rather than building models from scratch.
Architect scalable, cloud-native solutions on GCP and AWS, selecting the best language and tools for performance and maintainability — Python proficiency is expected, but technology choices should be driven by what is right for the problem.
Actively leverage AI coding assistants, LLMs (e.g., Claude, Gemini, GPT), and prompt engineering techniques to accelerate development, debug complex problems, and produce higher-quality code faster.
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Drive responsible AI practices across the team, including evaluating AI tool outputs, prompt governance, and ethical AI considerations.
Collaborate with product management, data science stakeholders, and QA to translate requirements into robust, well-tested technical implementations.
Define and enforce software engineering standards within a CI/CD environment, ensuring maintainable, testable, and reliable code.
Lead code reviews, architecture discussions, and technical planning sessions.
Mentor junior and mid-level engineers on AI development, cloud-native patterns, and disciplined engineering practices.
Stay current on emerging AI frameworks, LLM capabilities, and agentic design patterns to continuously raise the bar on what the team delivers.
Minimum Qualifications:
Bachelor's or Master's degree in Computer Science, Software Engineering, AI, or a related field.
5+ years of professional software engineering experience, with a demonstrated track record of staying ahead of the AI curve — actively adopting and applying AI tools, workflows, and capabilities as they have evolved.
Proficiency in Python; ability to architect solutions using the best possible languages for performance — technology selection should match the problem, not default to a single stack.
Hands-on experience applying AI/ML frameworks and services (e.g., TensorFlow, PyTorch, LangChain, or cloud-managed AI services) to real engineering problems.
Hands-on experience with GCP and/or AWS, including managed AI/ML and cloud infrastructure services.
Demonstrated ability to write effective prompts and use LLMs to accelerate development, automate workflows, and solve engineering problems.
Solid understanding of the software development lifecycle, agile methodologies, and CI/CD pipelines.
Experience with automated testing, deployment planning, and operating production software systems.
Strong communication, leadership, and cross-functional collaboration skills.
Preferred Qualifications:
Experience with agentic AI systems, multi-agent orchestration frameworks, or LLM-based automation workflows.
Familiarity with containerization and orchestration tools (Docker, Kubernetes).
Cloud or AI certifications (GCP Professional, AWS, or equivalent).
Prior experience in a DevOps or NetDevOps environment with AI integration.
ADDITIONAL INFORMATION
This role requires an engineer who can both contribute directly to complex features and elevate the technical capabilities of the team around them.
Strong AI literacy — including the ability to design prompts, critically evaluate model outputs, and integrate AI tooling into engineering workflows — is a non-negotiable expectation.
The candidate will be expected to model disciplined engineering practices while embracing AI-assisted development as a force multiplier for the entire team.
All work is conducted in adherence to Cisco security policy and compliance requirements, including responsible handling of data and AI-generated content.
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.
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