Staff/Senior Distributed Systems Engineer

About the role

Helios is building a new kind of company to solve America’s hardest problems, starting with the government interaction layer. Government shapes every consequential market, but the infrastructure connecting public institutions and private organizations remains fragmented, manual, and difficult to navigate. Helios is rebuilding that layer. Our core platform, Proxi, gives organizations the intelligence they need to understand what government is doing, why it matters, and what to do next. From that foundation, we design and deploy secure, mission-specific systems for government agencies, enterprises, and institutions operating in complex and highly regulated environments. We bring together frontier AI, deep public-sector expertise, and forward-deployed execution. Our team includes leaders and builders from the White House, U.S. Department of State, Datadog, and Microsoft. We are backed by leading institutional investors and trusted by organizations working on high-stakes problems across government and industry.

As a distributed systems engineer at Helios you will expand and operate the distributed execution, storage, scheduling, and reliability primitives that support data ingestion, document processing, search indexing, model inference, agents, and continuously running research workflows. The primary responsibility centers around the orchestration of critical infrastructure to meet mission-critical performance and reliability guarantees. Our platform runs a multitude of network crawling, compute grids, memory-heavy document processing, OCR, inference, and latency-sensitive jobs, all of which you should be familiar with.

Responsibilities

• Own the operation and architecture of Proxi’s distributed execution platform, covering ingestion, document processing, search index performance and long-running research jobs.
• Manage the deployment of our GovCloud and Air-Gapped resources for sensitive environments.
• Manage the orchestration of long-running agent research tasks including scheduling, lease management and retention.
• Queue optimization and cross-cloud information pipeline scalability.
• Build out dedicated resource-aware autoscaling architecture for fast search and