Senior Engineer, Cloud Infrastructure (US)

Assess each client's cloud infrastructure, data stack, and security perimeter before any build starts — translate findings into a concrete integration plan

Design and provision client environments using Terraform — networking, IAM, container orchestration, managed storage, and secrets management across GCP, AWS, or Azure depending on the client

Deploy and operate LLM inference pods in client cloud environments — managing API integration, rate limits, latency, and failure handling without needing a data scientist in the room

Build and maintain integration layers that connect client data sources to the AI layer — you own the plumbing that makes inference useful; the data science team owns what runs on top of it

Deploy and maintain containerized workloads via Helm — orchestration, ETL workers, and AI inference pods running inside the client's cloud perimeter

Own data pipeline deployments end to end — scheduling, pagination, retry logic, and rate-limit management against client API gateways

Manage distributed ETL jobs at scale — JSON flattening, schema enforcement, and structured output delivery

Enforce data residency requirements — raw data stays inside the client's environment, only structured output leaves to our shared infrastructure

Serve as the primary technical contact for each client's DevOps and infrastructure teams throughout the engagement

Lead technical working sessions with client teams — validate configurations, confirm IAM and credential models, review cluster specs before deployment

Triage and resolve pipeline and infrastructure failures across multiple client environments simultaneously

Implement container security standards — non-root execution, read-only filesystems, startup integrity hashes, tamper protection

Mentor junior and mid-level engineers and contribute implementation patterns to the shared playbook after every client engagement