AI Engineer

Job Description

AI Engineer

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

About Jobright

Jobright is innovating the job search experience by leveraging AI to provide a fast, expert-guided journey for users. Our mission is to transform how people find jobs, making the process more efficient and effective through intelligent automation and personalized assistance.

Why Join Us

• Build real, production AI agents used by real users, directly impacting their job search success.
• High ownership and impact, allowing you to significantly contribute to our core product and direction.
• Work at the exciting intersection of AI, agents, and product, pushing the boundaries of what’s possible.
• Shape how people experience AI-driven job search, contributing to a future where finding a job is seamless and intuitive.

Responsibilities

• Design, build, and maintain the scalable infrastructure required to deploy and serve production-grade AI agents, ensuring reliability and performance.
• Implement and optimize Large Language Model (LLM) pipelines, focusing on critical metrics such as latency reduction, throughput maximization, and efficient resource utilization.
• Develop automated systems for model monitoring, testing, and continuous integration (CI/CD) to ensure the ongoing reliability, accuracy, and performance of our AI agents.
• Optimize data ingestion and processing layers to support real-time agent responsiveness and complex RAG (Retrieval-Augmented Generation) architectures, enhancing the quality of AI interactions.
• Architect and refine APIs and backend services that seamlessly bridge the gap between sophisticated AI models and the intuitive, user-facing product experience.

Qualifications

Required

• Recent graduate or early-career professional (0–2 years of experience) with a degree in Computer Science, Software Engineering, or a related technical field.
• Strong proficiency in Python and practical experience with backend frameworks such as FastAPI, Flask, or Django.
• Practical experience with machine learning frameworks (PyTorch or TensorFlow) and a solid understanding of software engineering best practices (e.g., version control with Git, CI/CD principles, unit testing).
• Familiarity with the deployment of LLMs and a foundational understanding of the infrastructure required to support autonomous agents.
• Must live in and be authorized to work in the United States.

Preferred

• Previous internship or project experience in ML Ops, backend engineering, or distributed systems, particularly within an AI-focused company.
• Hands-on experience with containerization technologies (Docker, Kubernetes) and cloud infrastructure platforms (AWS, GCP, or Azure).
• Knowledge of vector databases (such as Pinecone, Milvus, or Weaviate) and their integral role in production AI systems.
• Strong foundation in both SQL and NoSQL database management for high-scale data handling and complex data models.