AI Engineer Position: Remotely Manage AI Shopping Agents
**Constructor Seeks Experienced AI Engineer for Agent Product Development**
Constructor, a U.S.-based ecommerce search and discovery platform, is on the hunt for an experienced AI Engineer to join their team. Founded in 2019 by Eli Finkelshteyn and Dan McCormick, Constructor powers over 1 billion queries every day across 150 languages and roughly 100 countries, serving major ecommerce companies like Sephora, Under Armour, and Petco.
The AI Engineer role at Constructor is a unique opportunity for a tech-savvy professional with a passion for large language models (LLMs), retrieval-augmented generation (RAG), and agentic system development. The successful candidate will design and build Constructor's Agent Products, focusing on developing and evaluating sophisticated RAG pipelines and agentic workflows.
To excel in this role, the AI Engineer will require a solid understanding of ML evaluation methodologies and key IR metrics, as well as experience with automatic prompt optimization techniques, such as DSPy. The engineer will own the end-to-end data lifecycle for AI workflows, including vector database ingestion and indexing.
The Constructor search engine is entirely invented in-house and utilizes transformers and generative LLMs. The AI Engineer will collaborate with various teams to translate AI capabilities into tangible, high-quality product features.
The tech stack for the AI Engineer position at Constructor includes Python, FastAPI, asyncio, Airflow, Luigi, PySpark, Docker, LangGraph, Vector Databases, DynamoDB, AWS S3, AWS RDS, AWS, Databricks, and Ray.
Constructor is committed to cultivating a work environment that is diverse, equitable, and inclusive. The company is an equal opportunity employer, welcoming individuals of all backgrounds and providing equal opportunities to all applicants regardless of their education, diversity of opinion, race, color, religion, gender, gender expression, sexual orientation, national origin, genetics, disability, age, veteran status, or affiliation in any other protected group.
The base salary range for the AI Engineer position at Constructor is between $80k and $120k USD. The benefits package includes unlimited vacation time, a fully remote team, a work from home stipend, Apple laptops provided for new employees, a training and development budget for every employee, maternity & paternity leave for qualified employees, regular team offsites, and diversity, equity, and inclusion initiatives.
To apply, candidates are encouraged to submit their applications, even if they don't meet all the listed qualifications. Constructor values the power of diverse perspectives and is committed to providing opportunities for growth and learning to all team members.
For more information about the AI Engineer role at Constructor, visit their website at [constructor.ai](http://constructor.ai).
References: [1] "The Future of AI Engineering." Medium, 2021, medium.com/@constructorai/the-future-of-ai-engineering-9d15b8c9633d. [2] "Constructor AI Raises $25 Million to Build a Better Search Engine." TechCrunch, 2021, techcrunch.com/2021/08/10/constructor-ai-raises-25-million-to-build-a-better-search-engine/. [3] "What Skills Does an AI Engineer Need?" Indeed, 2022, indeed.com/career-advice/finding-a-job/what-skills-does-an-ai-engineer-need. [4] "The Rise of Human-Centered AI." Forbes, 2021, forbes.com/sites/forbestechcouncil/2021/04/14/the-rise-of-human-centered-ai/?sh=42458e6767e8.
- The AI Engineer at Constructor will design and build Agent Products, focusing on developing and evaluating sophisticated Retrieval-Augmented Generation (RAG) pipelines and agentic workflows, as the Constructor search engine is entirely invented in-house and utilizes transformers and generative Large Language Models (LLMs).
- The successful candidate for the AI Engineer role at Constructor will need a solid understanding of Machine Learning (ML) evaluation methodologies and key Information Retrieval (IR) metrics, as they will own the end-to-end data lifecycle for AI workflows, including vector database ingestion and indexing, using a tech stack that includes Python, FastAPI, and various other tools.
