About Abaka

Abaka AI is built on one mission: to be the world's most trusted data partner for AI companies. More than 1,000 industry leaders across Generative AI, Embodied AI, and Automotive AI rely on us to power their data pipelines. With our headquarters in Silicon Valley—and teams in Paris, Singapore, and Tokyo—we support global partners with fast, reliable, and scalable data solutions.

Our offerings include a diverse catalog of off-the-shelf datasets (image, video, multimodal, reasoning, 3D, and beyond) as well as comprehensive data collection and annotation services. Whether teams need raw data, curated datasets, or full-cycle data engineering, Abaka AI provides the foundation for building high-performance AI systems.

About the Role

As a Member of Technical Staff, Infra, you'll own the scalability and reliability of the services that power our AI-native product features and platform applications, spanning our cloud infrastructure, APIs, and data models that need to hold up under real production load. Backend and infra will be your primary focus, but you should still be a generalist enough to support end-to-end product development when needed.

Finally, you are a product-minded engineer that cares as much about whether a feature solves the customer and users' problems as you do about how it's built. Our Expert Talent platform is growing and scaling significantly in the 1-100 stage, so your impact will be immense and have a great deal of ownership from day one.

Responsibilities

- Own the architecture of Abaka Expert Platform's shared backend systems—core services, data models, APIs, and cross-product infrastructure.

- Define and drive the long-term technical strategy for backend architecture across the organization.

- Design, build, and ship backend services and APIs that power AI-native product features at scale.

- Design systems for scale, reliability, and evolvability, and lead the highest-stakes technical decisions and design reviews.

- Establish backend engineering standards, patterns, and best practices adopted across all product teams.

- Partner closely with Product and AI/ML teams to translate product and model requirements into production-grade systems.

- Use modern AI development tools.

- Improve performance, reliability, and observability of existing backend infrastructure.

- Debug and resolve production issues.

Qualifications

- 3+ years of professional backend software engineering experience.

- Strong expertise in backend: API design, data modeling, distributed systems, databases, and API design at scale.