Job Description
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.
