AI Engineer

Job Description

AI Engineer | Jobright

The Tone:
This is an early career role at Jobright, located in the United States. Jobright is a personal AI job search agent that transforms the job search process into a fast, expert-guided journey. This role is crucial for building and scaling business-facing AI agents, managing their entire lifecycle from prototype to production. You will work at the intersection of AI, agents, and product, shaping how people experience AI-driven job search with high ownership and impact.

The TL;DR
• Role: Early Career
• Location: Remote, United States
• Mission: This person will build and scale production AI agents that power Jobright’s core job search functionality.
• Tech Stack: Python, PyTorch, TensorFlow, Scikit-learn, AWS, GCP, Azure, SQL

What You’ll Actually Do
• Develop: Develop and deploy predictive models and machine learning algorithms that power the core logic of Jobright’s production AI agents.
• Optimize: Experiment with and optimize Large Language Model (LLM) prompts, fine-tuning techniques, and RAG pipelines to improve agent performance and reliability.
• Analyze: Perform deep-dive statistical analysis on user interaction data to identify patterns that drive product improvements and feature innovation.
• Monitor: Monitor model performance and provide technical support during critical product iteration cycles.

The Must-Haves
• Background: Recent graduate or entry-level professional (0–2 years of experience) with a degree in Data Science, Computer Science, Statistics, or a related quantitative field.
• Experience: Strong programming skills in Python; practical understanding of LLM architectures, prompt engineering, and the evaluation of generative AI outputs.
• Skills: Python, machine learning libraries (PyTorch, TensorFlow, Scikit-learn), LLM architectures, prompt engineering, generative AI output evaluation, strong communication.
• Bonus: Previous internship or research experience focused on Natural Language Processing (NLP), autonomous agents, or recommendation systems; experience building and maintaining data pipelines and working with cloud infrastructure (AWS/GCP/Azure); strong technical foundation in SQL and database management.