Senior Cloud Engineer (GCP)

Type: Full-time, Permanent

About the role

We're a deep-tech and engineering company building a Silicon Valley-funded biomedical wearable, now approaching launch. The product is a hardware device paired with a companion mobile app: the app streams physiological data to the cloud, where our algorithms process it and return results for the user.

We're adding a small but senior software group in Lahore alongside our embedded and algorithm engineers. This is the cloud/backend/DevOps seat. You'll own the server side of that pipeline end to end. It's an autonomous role with room to grow as the product and team scale.

• Design, build, and operate the cloud backend that ingests real-time data from the wearable companion app and returns processed results.
• Own the API layer between the mobile apps and the cloud.
• Productionize, deploy, and scale the processing/analytics workloads authored by the algorithm team — reliability, latency, and cost.
• Build the data pipeline: ingestion, storage, processing, and delivery back to the app.
• Own DevOps: CI/CD, infrastructure-as-code, observability, and on-call reliability.
• Apply strong security and data-handling practices appropriate to health data.
• Work closely with embedded, algorithm, and mobile engineers across the product.

• Solid backend engineering plus hands-on cloud and DevOps experience — comfortable owning a service from design through production.
• Experience with Google Cloud (GCP); containerized deployment (Docker) and orchestration (GKE/Kubernetes) preferred.
• API design and building reliable data pipelines, ideally with real-time or streaming data.
• CI/CD, infrastructure-as-code (Terraform or similar), monitoring, and a reliability mindset.
• Sound instincts on security, access control, and handling sensitive data.
• Able to work autonomously in a small senior team, onsite in Lahore.

• Healthcare, biomedical, or other regulated-data experience.
• IoT / device-to-cloud data pipelines.
• Experience productionizing ML or algorithmic workloads (MLOps-adjacent).

• A small, senior, high-ownership team — direct impact, short feedback loops, and the autonomy to own your work end-to-end.
• Learn among domain experts — the team includes several PhDs and industry veterans. As the cloud owner embedded with them, you'll work on hard problems that have real impact on people's lives.
• Autonomy and room to grow — a small, senior team where you shape the architecture and take on more as the product and team scale.