Senior Software Engineer, Connectivity

Scale AI•San Francisco, CA

About The Position

Senior Software Engineer, Platform — Connectivity The Connectivity team owns the core platform that enables Scale to continuously generate, evaluate, and deliver high-quality training data to our customers. Our systems sit at the center of Scale’s data and AI infrastructure, powering large-scale workflows while supporting frontier AI capabilities such as multi-modality, long-horizon reasoning, and agentic behavior. We’re looking for a senior engineer with deep experience building robust platforms, someone who brings strong architectural judgment, a bias toward correctness and reliability, and the ability to design systems that scale and evolve cleanly over time. This is a backend-heavy role with full-stack expectations and significant ownership from design through long-term operation.

Requirements

7+ years of professional software engineering experience, with a strong background in building and operating large-scale, production-grade platforms.
Deep expertise in distributed systems and cloud-native architectures, including Kubernetes, microservices, event-driven systems, caching, and production databases.
Proven ability to lead multi-quarter technical initiatives, work effectively across cross-functional teams, and apply strong architectural judgment in ambiguous environments.

Nice To Haves

Experience integrating with public LLM APIs and designing systems that handle scale, reliability, latency, and cost tradeoffs.
Experience building or operating data processing and transformation systems supporting complex workflows and evolving schemas.

Responsibilities

Design and own foundational platform systems that support scalable data generation, evaluation, and bespoke customer delivery across Scale’s ecosystem.
Architect extensible, production-grade services that can support frontier AI workflows, including multi-modal inputs, long-running processes, and agentic orchestration.
Build and operate distributed systems at scale, with strong guarantees around correctness, reliability, observability, and cost efficiency.
Integrate with public LLM APIs and AI services, designing abstractions that are resilient to model churn, latency variability, and evolving usage patterns.
Design and maintain data transformation and processing systems, supporting complex schema evolution, customization, and high-throughput workloads.
Partner closely with infrastructure, product, and customer-facing teams to define requirements, shape technical direction, and deliver seamless integration experiences for customers.
Lead multi-quarter technical initiatives, including authoring and driving a 6+ month technical roadmap for major platform investments.
Apply strong engineering judgment in ambiguous problem spaces, balancing speed with long-term maintainability and operational excellence.
Raise the quality bar through thoughtful system design reviews, rigorous code reviews, and mentorship grounded in real-world production experience.