Senior Software Engineer, Streaming

Crusoe•San Francisco, CA

2d•$172,000 - $209,000

About The Position

Crusoe is on a mission to accelerate the abundance of energy and intelligence . As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster. We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI. We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services. If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe. About This Role We’re looking for a Senior Streaming Software Engineer to join the Observability team within our Cloud Infrastructure organization. This team builds and operates the real-time data platforms that power metrics, logs, traces, and event streams used by engineers across the company to understand and operate Crusoe’s AI cloud reliably at scale. In this role, you’ll design, build, and operate high-throughput streaming systems that process massive volumes of telemetry data generated across our GPU cloud and global data centers. Your work will help ensure engineers have real-time visibility into complex distributed systems and the infrastructure that powers them. This is an opportunity to work on large-scale data pipelines and distributed systems that power observability across a rapidly scaling AI cloud environment.

Requirements

Strong experience building and operating distributed systems, especially streaming or real-time data platforms
Hands-on experience with Kafka or similar distributed streaming technologies
Proficiency in backend languages such as Java, Scala, Go, or Python
Experience operating services in cloud or large-scale infrastructure environments
Solid understanding of observability fundamentals including metrics, logging, tracing, and alerting
Comfort debugging production issues across distributed systems
Ability to own features end-to-end, from design through production operations
Strong collaboration skills and a pragmatic engineering mindset

Nice To Haves

Experience building observability platforms at cloud or data center scale
Familiarity with stream processing frameworks and delivery semantics
Experience with Kubernetes and containerized infrastructure
Exposure to schema management, data contracts, or serialization formats
Experience working with bare-metal infrastructure or large-scale data center environments
Interest in mentoring junior engineers

Responsibilities

Designing, building, and maintaining streaming services and pipelines that ingest and process observability data including logs, metrics, traces, and operational events
Implementing real-time data processing systems using technologies such as Kafka, Kinesis, Pub/Sub, Flink, or similar streaming platforms
Scaling streaming infrastructure to support high-throughput telemetry ingestion, high-cardinality workloads, and bursty infrastructure traffic patterns
Ensuring streaming systems are reliable and observable, with strong instrumentation, dashboards, and alerting
Collaborating with SREs and platform teams to integrate streaming data into internal observability tools and operational workflows
Participating in on-call rotations, incident response, and post-incident reviews
Improving system reliability and developer experience through automation, CI/CD, and infrastructure-as-code practices
Contributing to technical design discussions and reviews for new streaming capabilities

Benefits

Industry competitive pay
Restricted Stock Units in a fast growing, well-funded technology company
Health insurance package options that include HDHP and PPO, vision, and dental for you and your dependents
Employer contributions to HSA accounts
Paid Parental Leave
Paid life insurance, short-term and long-term disability
Teladoc
401(k) with a 100% match up to 4% of salary
Generous paid time off and holiday schedule
Cell phone reimbursement
Tuition reimbursement
Subscription to the Calm app
MetLife Legal
Company paid commuter benefit; $300 per month