About Clip
Clip Automation is an Industry 4.0 company revolutionizing manufacturing operations worldwide. Based in Silicon Valley and founded by former Apple and Juul engineers with 25+ years of experience solving efficiency, productivity, and manufacturing challenges in high-volume production, Clip brings people, processes, and machines together.
Our SaaS platform, ClipSuite, spans cloud and edge and leverages IoT, AI, and ML to deliver industrial data extraction, remote asset video monitoring, real-time collaboration, machine-driven data, and detailed reporting — all in one customizable, user-friendly system. Learn more at clipautomation.com.
The Opportunity
ClipSuite ingests high-frequency data from thousands of machines, PLCs, sensors, and cameras on factory floors around the world. We're looking for a Staff Engineer to own the architecture of that backbone — the distributed systems that move real-time telemetry from the edge to the cloud reliably, at low latency, and at scale.
This is a hands-on technical leadership role. You'll set the technical direction for our IoT and streaming platform, write critical-path code, and raise the engineering bar across the team. If you've built systems where dropped messages and seconds of lag actually matter, we want to hear from you.
What You'll Do
- Architect, build, and operate distributed systems that ingest, process, and serve real-time telemetry from industrial IoT devices at scale
- Own the edge-to-cloud data path: device connectivity, edge gateways, message brokers, stream processing, and storage
- Design for reliability in hostile environments — intermittent connectivity, store-and-forward, back-pressure, out-of-order and duplicate data
- Drive scalability and performance: throughput, latency, horizontal scaling, multi-tenant isolation, and cost efficiency
- Define and champion observability (metrics, tracing, logging, alerting) and SLOs for the platform
- Lead design reviews and write technical specs that shape the roadmap; make and document key build-vs-buy and architectural decisions
- Partner with Product, Data, Network, and Frontend teams to deliver end-to-end features — from machine signal to dashboard
- Mentor engineers, set coding and operational standards, and lead incident response and postmortems
- Thrive in a startup: wear many hats and grow with the company
What You'll Bring
- Bachelor's degree in Computer Science or related field, or equivalent experience
- 10+ years of software engineering experience, including 4+ years designing and operating large-scale distributed systems in production
- Deep expertise in one or more of: Go, Java, Scala, Rust, C++, or Python
- Hands-on experience with streaming and messaging systems such as Apache Kafka/Confluent, MQTT, NATS, or Kinesis
- Strong grasp of distributed systems fundamentals — consistency, partitioning, replication, fault tolerance, and exactly-/at-least-once semantics
- Experience with time-series data and high-throughput storage (e.g., TimescaleDB, InfluxDB, ClickHouse, Cassandra)
- Production experience on AWS (or another major cloud) with containers and orchestration (Docker, Kubernetes)
- A track record of leading cross-team technical initiatives and mentoring engineers
Nice to Have
- Industrial IoT protocols: OPC UA, Modbus, MQTT Sparkplug B, EtherNet/IP
- Edge computing frameworks (AWS IoT Greengrass, Azure IoT Edge, K3s)
- Stream processing with Flink, Spark Streaming, or Kafka Streams
- Video streaming or media pipelines
- Manufacturing, production, or operations environment experience
Travel
Occasional customer site visits, as required.
Location & Work Model
Indianapolis, IN or Fort Worth, TX or SF Bay Area Preferred. Remote accepted.
Bay Area candidates are strongly preferred.
Compensation & Benefits
[Base salary range: US Based $180K-$225K ] + equity. Adjusted based on foreign location.
Competitive benefits package including medical, dental, vision, life insurance, and 401(k).
Equal Opportunity
- Clip is an equal opportunity employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status.