Dropbox is a global community focused on creating more enlightened ways of working. They are seeking a Senior Infrastructure Software Engineer to design and build core systems for their AI-first productivity product, Dropbox Dash, with a focus on orchestration and evaluation infrastructure.
Responsibilities:
- Design and build the orchestration and planning systems that power Dropbox’s agent platform, including task decomposition, scheduling, and error recovery
- Implement real-time execution frameworks that allow multiple agents and tools to coordinate and act reliably at scale
- Develop clean, extensible APIs, data models, and protocols that enable new agent capabilities to plug seamlessly into the platform
- Build and maintain the evaluation platform used to measure agent performance (accuracy, latency, cost, safety, satisfaction) and catch regressions
- Establish and improve observability, testing, and debugging workflows for agentic systems in production
- Collaborate with AI research, infra, and product teams to translate high-level product goals and research insights into robust, production-ready systems
- Contribute to technical roadmaps, design docs, and architecture reviews, helping set direction for agent platform and eval platform evolution
Requirements:
- 9+ years of professional software engineering experience, including significant experience building production-scale systems or platforms
- Proven experience building or operating orchestration, workflow, or scheduling systems (e.g., task graphs, workflow engines, pipelines)
- Strong technical understanding of system design, service reliability, fault tolerance, API design, and observability
- Demonstrated ability to drive complex technical projects end-to-end and work effectively across research, infra, and product teams
- Strong analytical and problem-solving skills with a focus on measurable outcomes (latency, throughput, reliability, cost)
- Excellent written and verbal communication skills, with the ability to explain design decisions and influence technical direction across teams
- Experience building or working with agentic AI systems (e.g., multi-step reasoning workflows, tool orchestration, planning frameworks, retrieval-augmented generation)
- Background in evaluation systems for LLMs or agentic workflows (e.g., quality metrics, automatic evaluation pipelines, human-in-the-loop feedback)
- Prior work on developer platforms, SDKs, or frameworks used by other engineers to build on shared infrastructure
- Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience