AI Engineer

Mercari, Inc.

full-time

Posted on: 9/18/2025

Origin: • 🇮🇳 India

✨ AI Apply

JuniorMid-Level

AWSCloudDockerGoGoogle Cloud PlatformKubernetesPython

About the role

Design, develop, and deploy innovative AI applications using foundation models (LLMs, Multimodal Models) across Mercari.
Build foundational platforms and services enabling product teams to ship scalable AI features.
Build Foundational AI Services using prompt engineering, RAG, and fine-tuning to solve high-impact problems.
Collaborate with product, engineering, and infrastructure teams to integrate AI into the Mercari app and architect modular scalable solutions.
Develop evaluation pipelines to measure, monitor, and improve model performance focusing on accuracy, latency, cost, and responsible AI.
Own features end-to-end: problem scoping, prototyping, production deployment, maintenance, and iteration based on metrics and user feedback.
Stay at the forefront of AI engineering advancements and share knowledge to uplift organization capabilities.

2-6 years of professional software engineering experience, with a demonstrated focus on building and deploying AI/ML-powered systems in production.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Proficiency in Python and hands-on experience building applications with Large Language Models (LLMs) and familiarity with core concepts such as prompt engineering, RAG, and fine-tuning.
Experience building Model Context Protocol(MCP) servers in either Python or Go.
Solid understanding of software engineering fundamentals and the ability to write clean, maintainable, and production-ready code.
Strong problem-solving skills and a data-driven approach to decision-making.
Excellent communication skills to collaborate effectively with both technical and non-technical stakeholders across multiple teams.
Preferred Skills:
Experience designing and implementing systematic evaluation strategies for generative AI systems (e.g., AI-as-judge, human-in-the-loop).
Experience with cloud platforms (GCP, AWS, etc.) and containerization technologies (Docker, Kubernetes).
Contributions to open-source projects or publications in top-tier AI/ML conferences.
Experience with microservice architecture and development.