CarGurus

Principal AI Engineer, AI Solutions

CarGurus$172K — $216K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 8+ years of relevant software engineering experience (no degree required)
  • Strong software engineering fundamentals with a history of building production systems
  • Proficiency in Python as the primary programming language
  • Experience designing APIs, services, and data pipelines with a systems-thinking approach
  • Fluency with AWS and its infrastructure/services
  • Hands-on experience with LLM APIs and AI-powered applications in production
  • Ability to work autonomously and make architectural decisions

Responsibilities

  • Design and build AI-powered workflows that transform team operations
  • Partner with stakeholders to gather requirements and identify AI opportunities
  • Build end-to-end solutions from scoping to deployment
  • Work with AI APIs and platforms to create intelligent tooling
  • Navigate a complex environment and build without waiting for ideal conditions
  • Help shape technical strategy and standards for AI Solutions

Benefits

  • Comprehensive Total Rewards Package
  • Eligibility for discretionary bonuses and incentives
  • Potential for Restricted Stock Units (RSUs)
Full Job Description
Role Overview

CarGurus is transforming how the company operates by embedding AI into workflows across every function - product, engineering, revenue, finance, support. It's a software engineering role where the domain is the entire business. You'll work directly with teams across the org to understand how work actually gets done, identify where AI can change the unit of work or shift where judgment lives, and build the systems that make it real. Some of that is agent-based automation. Some of it is workflow redesign. All of it requires someone who can architect and ship production-quality software, not stitch together SaaS integrations. This is not a Salesforce developer, Boomi connector, or low-code/no-code position, nor is it an enterprise architect or ML model training role.

This is a small, high-autonomy team reporting to the Head of AI Solutions. You'll have outsized influence on how a publicly traded company with ~$1B in revenue adopts AI - not as a pilot or a demo, but as a structural change in how the business runs. You will be successful here if you are a product-caliber engineer who finds internal workflow transformation genuinely interesting - not a consolation prize, but the most leveraged place to be right now. You'd rather build something real that 200 people use tomorrow than something polished that ships in 6 months.
What You'll Do
  • Design and build AI-powered workflows and agent-based systems that transform how teams operate across the company.
  • Partner directly with stakeholders in revenue, product, engineering, finance, and operations to gather requirements, map existing workflows, and identify high-leverage opportunities for AI.
  • Build end-to-end - from scoping and architecture through implementation and deployment. This team ships, it doesn't hand off specs.
  • Work with AI APIs and platforms (Anthropic/Claude, AWS Bedrock, and others) to build agentic systems, automation pipelines, and intelligent tooling.
  • Operate across a messy, heterogeneous environment - AWS infrastructure, Salesforce, internal services - without waiting for everything to be clean before you start building.
  • Help shape the technical strategy and standards for AI Solutions as a function.
What You'll Bring

Must-haves:
  • 8+ years of relevant software engineering experience (no degree required; equivalent experience is fully accepted).
  • Strong software engineering fundamentals - you've built and shipped production systems, not just prototypes.
  • Proficiency in Python as the primary language for this work; comfort with additional languages is a plus.
  • Experience designing APIs, services, and data pipelines. You think in systems, not scripts.
  • AWS fluency - you're comfortable working within AWS infrastructure and services.
  • Hands-on experience building with LLM APIs, agent frameworks, or AI-powered applications - not just experimentation, but something that ran in production or was used by real people.
  • Ability to operate with high autonomy. You'll scope your own work, make architectural decisions, and own outcomes.
  • Willingness to work across the full stack of a business - including systems like Salesforce that aren't glamorous but are where the high-impact problems live.

Nice-to-haves:
  • Experience with workflow orchestration or automation at scale.
  • Familiarity with Salesforce APIs and integration patterns (not Salesforce administration).
  • Background in recommendations, search, data science, or ML engineering.
  • Experience working cross-functionally with non-technical stakeholders.


The displayed range represents the expected annual base salary / On-Target Earnings (OTE) for this position. On-Target Earnings (OTE) is inclusive of base salary and on-target commission earnings, which applies exclusively to sales roles.

Individual pay within this range is determined by work location and other factors such as job-related skills, experience, and relevant education or training.

This annual base salary forms part of a comprehensive Total Rewards Package. In addition to benefits, this role may qualify for discretionary bonuses/incentives and Restricted Stock Units (RSUs).

Position Pay Range

$172,000-$216,000 USD

About CarGurus

CarGurus is an online automotive marketplace that allows users to search for and compare new and used cars. The company was founded in 2006 and is headquartered in Cambridge, Massachusetts. CarGurus has a strong focus on transparency and provides users with information on pricing, dealer reputation, and vehicle history. The company has been recognized for its innovative approach to car shopping and has won several awards for its platform.
Learn more about CarGurus
Size
1,203 employees
Market Cap
$1.5 billion
Industry
Net Income
$77.5 million
Founded
2006
5 Year Trend
+36.9%
Revenue
$551.4 million
NASDAQ

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