We're looking for a senior software engineer to join our Connectivity team, which 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 centre 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 behaviour.
As a senior software engineer, you will design and own foundational platform systems that support scalable data generation, evaluation, and bespoke customer delivery across Scale's ecosystem. You will architect extensible, production-grade services that can support frontier AI workflows, including multi-modal inputs, long-running processes, and agentic orchestration. You will build and operate distributed systems at scale, with strong guarantees around correctness, reliability, observability, and cost efficiency.
You will integrate with public LLM APIs and AI services, designing abstractions that are resilient to model churn, latency variability, and evolving usage patterns. You will design and maintain data transformation and processing systems, supporting complex schema evolution, customization, and high-throughput workloads. You will partner closely with infrastructure, product, and customer-facing teams to define requirements, shape technical direction, and deliver seamless integration experiences for customers.
You will lead multi-quarter technical initiatives, including authoring and driving a 6+ month technical roadmap for major platform investments. You will apply strong engineering judgment in ambiguous problem spaces, balancing speed with long-term maintainability and operational excellence. You will raise the quality bar through thoughtful system design reviews, rigorous code reviews, and mentorship grounded in real-world production experience.
Ideal Experience:
- 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.
Preferred Experience:
- 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.
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