Lead Data Scientist

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Cisco

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1984

🔧 Hardware

🔐 Security

🏢 Enterprise

Hardware • Security • Enterprise

Cisco is a multinational technology company that provides networking hardware, software, and services to enterprises, service providers, and governments. It builds routers, switches, optical transceivers, programmable silicon, and edge computing platforms, and offers security, collaboration (Webex), observability, and AI-enabled software and support services to help organizations design, operate, and secure large-scale networks and data centers. Cisco also delivers professional services, training, and cloud-managed solutions to support digital transformation and AI-ready infrastructure.

📋 Description

• Own the technical architecture and engineering strategy for AutoQuote's cloud-native platform — spanning AI feature integration, data pipeline infrastructure, microservices design, and platform reliability. • Lead the design and delivery of the highest-complexity, highest-impact engineering initiatives on the team, setting the architectural patterns and engineering standards that guide the broader organization. • Define and enforce software quality standards, AI usage guidelines, and engineering best practices across the AutoQuote engineering organization. • Partner with engineering leadership, product management, and program stakeholders to translate program strategy into a coherent technical roadmap and prioritized backlog. • Evaluate, prototype, and champion emerging AI capabilities — including LLM integration, agentic frameworks, and AI-assisted development tooling — driving adoption across the team and into the product. • Drive responsible AI governance across AutoQuote, including prompt engineering standards, AI output evaluation practices, and compliance with Cisco security and data handling policies. • Mentor and technically develop senior and mid-level engineers; serve as the primary technical authority and critical issue point for complex engineering decisions. • Lead architecture reviews, critical design decisions, and cross-functional technical alignment sessions. • Represent AutoQuote engineering in program-level and executive forums; communicate technical tradeoffs, risks, and decisions with clarity to both technical and non-technical audiences.

🎯 Requirements

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field; advanced degree preferred. • 8+ years of professional software engineering experience, with a demonstrated track record at the principal, staff, or distinguished engineer level. • Deep proficiency in Python; demonstrated ability to architect polyglot, cloud-native solutions — technology selection should always be driven by what is right for the problem, not a single prescribed stack. • Proven expertise in cloud-native architecture on GCP and/or AWS, including Kubernetes, distributed systems, managed AI/ML services, and data pipeline infrastructure. • Extensive hands-on experience applying AI/ML services and frameworks (LLM APIs, LangChain, cloud-managed AI services) in production engineering environments. • Demonstrated mastery of LLMs as engineering tools — prompt engineering, AI-assisted development, model output evaluation, and designing AI-powered workflows and agentic systems. • Track record of setting technical standards, driving architecture decisions at a program or organization level, and leading cross-functional engineering initiatives. • Strong technical communication skills — able to write crisp technical proposals, represent engineering tradeoffs to executive stakeholders, and influence without direct authority. • Experience operating and improving high-availability production systems at enterprise scale.

🏖️ Benefits

• All work is conducted in alignment to Cisco security policy and compliance requirements, including responsible handling of data and AI-generated content.