Cargurus Senior Principal Software Development Engineer in Consumer Commerce at CarGurus focusing on AI-driven consumer experiences. Lead technical direction and mentor engineers while deploying AI solutions at scale.
Responsibilities
CarGurus is hiring for a software engineer in our Consumer Commerce department – the group responsible for our highest trafficked pages and products. Our mission is to deliver comprehensive, accurate, and engaging vehicle information, fostering trust and driving informed and high-intent consumer decisions, while upholding CarGurus’ standards for innovation, user-centricity, and technical excellence. In this role, you’ll contribute to high‐visibility parts of our site, introduce AI to our consumer experiences, and collaborate closely with partners in Product, UX, and Analytics. This is a fast-moving, impact-oriented environment where you will set technical direction across the department, mentor engineers, and drive high-visibility AI initiatives from concept to production at scale.
Design, build, and deploy consumer-facing experiences end-to-end to 45 million monthly visitors, from the data and model layer through to the user-facing product, being hands-on and actively participating in the implementation of select initiatives
Serve as a go-to AI expert and advisor for all Consumer AI projects, providing technical guidance on architecture, design, and implementation choices
Guide the platform and infrastructure decisions underpinning AI deployments, including storage, memory, request handling and load, evaluation pipelines, observability and analytics
Evaluate the broader AI framework and tooling landscape, independent of any single language or ecosystem, and guide teams toward the right approach for a given problem; develop proof-of-concepts to validate AI approaches and clearly explain the trade-offs between different technologies
Build and operate systems using LangChain, LangGraph, and Langfuse in Python to develop, orchestrate, and evaluate agentic and LLM-based applications in production
Drive the department's adoption of fully agentic programming, defining the patterns, tooling, and best practices engineers follow when building agentic systems
Partner with engineering leadership, product, and data teams to shape phased platform guidelines and roadmaps for consumer initiatives
Mentor engineers across teams on system design, evaluation methodology, and operational best practices
Conduct workshops and produce documentation on AI development, deployment, monitoring, and support practices across multiple teams
Document architectural decisions in Architecture Decision Records (ADRs) and share findings and best practices across teams
