Software Development Engineer

About Us

WriftAI is building the infrastructure layer that makes AI easy to deploy and scale in production. We help teams ship AI-powered products faster by removing the operational complexity behind running models at scale — enabling customers to focus on building, not infrastructure. Our platform provides simple APIs and SDKs that handle model deployment, scaling, and performance optimization behind the scenes, making production-grade AI accessible to engineering teams of all sizes.

The Role

We’re looking for a Software Development Engineer to help build and evolve the core systems that power the WriftAI platform. This role focuses on developing product-facing services, APIs, and internal systems that enable developers to deploy, manage, and scale AI workloads reliably.

You’ll work closely with Platform Engineers, Product, and other engineers to deliver features that are robust, scalable, and easy to use.

What You'll Do

• Design and build backend services and APIs that power WriftAI’s core platform.
• Build and evolve systems that integrate directly with AI model inference, configuration, and lifecycle management.
• Implement features that improve reliability, performance, and usability for developers.
• Work hands-on with AI-powered features, experimenting with model behavior, performance characteristics, and developer-facing interfaces.
• Collaborate with Platform Engineers to integrate application logic with underlying infrastructure.
• Contribute to system design and architecture discussions.
• Debug and resolve issues across services in production environments.
• Write clear, maintainable, and well-tested code.

Minimum Requirements

• Strong software engineering experience (3+ years) building backend or distributed systems.
• Experience designing and maintaining APIs or backend services in production environments.
• Proficiency in at least one backend programming language (e.g., Go, Python, Java, or similar).
• Understanding of system design, performance considerations, and reliability best practices.
• Comfortable working independently and collaboratively in a fast-paced startup environment.

Nice to have

• Experience working hands-on with AI-powered systems, such as integrating model inference, experimenting with prompts or configurations, or building features on top of AI models.
• Familiarity with cloud-based systems or distributed architectures.
• Experience building or supporting high-throughput systems, data pipelines, or AI-powered products.
• Familiarity with observability tools and production debugging workflows.