Senior AI Platform Engineer ( Enterprise Systems)

Senior engineer who ships production software and AI systems on cloud infrastructure that is reliable, secure, and cost-disciplined. You design applications and services, operate inference platforms and pipelines, and treat unit economics (tokens, GPU-hours, idle capacity) as engineering constraints.

You partner with product, engineering, and business stakeholders to deliver working software, higher reliability, and lower cost per unit of AI value.

Required

5+ years of professional software development, owning production systems (not only scripts or notebooks).

Shipped backend services/APIs and production AI/ML (LLMs, RAG, serving).

Strong Python plus a second stack; PyTorch, TensorFlow, or equivalent serving.

AWS or GCP with Kubernetes, Terraform, and CI/CD.

Proven work reducing or governing cloud/AI spend.

Clear communication of technical and cost tradeoffs; you run what you build.

Preferred

Full-stack (React/Next.js), vector databases, inference optimization, FinOps tooling, SOX/SOC 2, Copilot/Cursor.

Production software and AI with SLOs and real ownership — not demos.

Reliability stays high while GPU and cloud waste trends down.

Cost per unit of AI value is visible and improving; teams reuse libraries, IaC, and cost guardrails.

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