AI Engineer

About Jobright.ai

Jobright is your personal AI job search agent that transforms the job search process into a fast, expert-guided journey. We are seeking an AI Engineer to build and scale business-facing AI agents, managing their entire lifecycle from prototype to production.

Why Join Jobright.ai?

• Build real, production AI agents used by real users.
• Experience high ownership and significant impact on product development.
• Work at the cutting-edge intersection of AI, autonomous agents, and product innovation.
• Directly shape how people experience AI-driven job search solutions.

Responsibilities of an AI Engineer

• Build and refine autonomous AI agents designed to interact with complex environments and solve real-world user problems.
• Develop and optimize sophisticated prompt engineering workflows and multi-agent orchestration frameworks to significantly enhance product capabilities.
• Integrate Large Language Models (LLMs) into the Jobright application, ensuring high-quality, low-latency, and reliable AI responses.
• Collaborate at the intersection of product and engineering to transform user requirements into functional, AI-driven features.
• Implement Retrieval-Augmented Generation (RAG) systems and fine-tune models to improve the accuracy and context-awareness of our AI agents.

Qualifications

Required

• Recent graduate or entry-level professional (0–2 years of experience) with a degree in Computer Science, AI, or a related technical field.
• Strong proficiency in Python and hands-on experience working with LLM APIs (such as OpenAI, Anthropic, or open-source models via Hugging Face).
• Practical understanding of agentic workflows, prompt chaining, and the latest trends in generative AI.
• Solid software engineering foundations, including a strong grasp of APIs, asynchronous programming, and version control (Git).
• Must live in and be authorized to work in the United States.

Preferred

• Previous internship or personal project experience building AI-powered applications, chatbots, or autonomous agents.
• Familiarity with agent frameworks such as LangChain, AutoGPT, or CrewAI.
• Experience with vector databases and semantic search implementation.
• Basic understanding of front-end or full-stack integration to help bridge the gap between AI logic and user interfaces.

Key skills/competency

• AI Agent Development
• Prompt Engineering
• LLM Integration
• Retrieval-Augmented Generation (RAG)
• Python Programming
• Generative AI Trends
• Software Engineering Fundamentals
• Asynchronous Programming
• Git Version Control
• Multi-agent Orchestration