Data Platform Engineer I — Build Scalable AI Data Systems

United States Digital Space LLC; United States; Remote; USD 122,000 - 176,000; Full time

Benefits offered by this job

Bonus or incentive compensation

Equity

Comprehensive benefits package

Job summary

Abnormal AI is seeking a Software Engineer I to design and operate components of a scalable data platform. You will work with engineers to build tools that enable teams to adopt and scale data systems, automate infrastructure, and apply GenAI techniques for smarter experiences.

Join a fast-growing, AI-first company where you can own end-to-end features, collaborate across teams, and grow your skills early in your journey while contributing to reliable, high-performance data workloads.

Qualifications

• 1+ years of software engineering experience.
• Solid programming skills in Python or Go.
• Fundamentals: data structures, clean code, testing, debugging.
• Interest in learning AWS, Databricks and related tech.
• Ability to work independently and in a team with good communication.

Responsibilities

• Contribute to design, development, and operation of core data platform components.
• Build tools and services to help other teams adopt and scale data systems.
• Automate infrastructure and operations for reliability and performance.
• Apply GenAI techniques to improve developer/operator experiences.
• Collaborate across engineering teams to address scalability challenges.
• Take ownership of projects and deliver features end-to-end with guidance.

Skills

Python

Go

Distributed systems

Backend engineering

Tools

AWS

Databricks

Kafka

Kinesis

Job description

Abnormal AI is seeking a Software Engineer I to design and operate components of a scalable data platform. You will work with engineers to build tools that enable teams to adopt and scale data systems, automate infrastructure, and apply GenAI techniques for smarter experiences.

Join a fast-growing, AI-first company where you can own end-to-end features, collaborate across teams, and grow your skills early in your journey while contributing to reliable, high-performance data workloads.