This is a unique opportunity for an early-career engineer who enjoys solving practical problems, building impactful tools, and working closely with data, AI, and operations teams. In this role, youll design and develop scalable internal platforms, automation systems, and AI-driven workflows that support large-scale data operations, including tooling for computer vision workflows, automated QA systems, taxonomy management, and database navigation tools used daily across the company.
As part of a fast-moving startup and an industry leader in AI-driven creative analytics, your work will have a direct impact on engineering efficiency, workflow automation, system scalability, and data quality.
Key Responsibilities
Design, develop, and maintain internal tools and systems that support Data Operations workflows.
Build scalable automation systems for QA processes, taxonomy applications, and large-scale data handling.
Collaborate closely with Data, AI, Product, and Operations teams to solve practical business and operational challenges.
Write clean, maintainable, and reliable code with a strong focus on usability, scalability, and efficiency.
Improve internal workflows by identifying bottlenecks and building scalable solutions.
Work with databases and data pipelines to support operational and analytical needs.
Troubleshoot issues, optimize existing tools, and continuously improve system reliability and performance.
Contribute ideas, experiment with new technologies, and help improve developer workflows and internal processes.
1-2 years of software engineering experience.
Strong programming fundamentals and problem-solving skills.
Comfort working with data-intensive systems and operational workflows.
Experience with Python, automation scripting, SQL, and relational databases.
Exposure to AI tools, computer vision, machine learning workflows, or data pipelines – a plus.
Experience building internal tools, platforms, or automation systems – a plus.
Pragmatic, proactive, and adaptable mindset with a strong sense of ownership and execution.
Curiosity about data operations, AI workflows, and internal tooling in a fast-paced startup environment.
Strong written and verbal communication skills in English.
