Senior Infrastructure Software Engineer, Dash

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