Senior AI Platform Engineer

Job summary

Build and operate production software and AI systems on reliable, secure, cost-disciplined cloud infrastructure, owning services, applications, inference platforms, and pipelines from development through maintenance. Develop APIs and productionize RAG, evaluation, fine-tuning, and model serving; architect AWS or GCP environments using Kubernetes and Terraform; manage observability and incident response; and improve cost efficiency by optimizing GPU use, inference routing, and cloud resources.

Benefits

Qualifications

• At least five years of professional software development experience owning production systems.
• Experience shipping backend services or APIs and production AI/ML systems, including LLMs, RAG, or model serving.
• Strong Python skills and proficiency in a second stack; experience with PyTorch, TensorFlow, or equivalent serving technology.
• Experience with AWS or GCP, Kubernetes, Terraform, and CI/CD.
• Demonstrated experience reducing or governing cloud and AI spending.
• Ability to communicate technical and cost tradeoffs and operate systems you build.

Responsibilities

• Design, build, and ship production services, APIs, and user-facing interfaces as needed.
• Own the software lifecycle, including implementation, testing, code review, CI/CD, deployment, and maintenance.
• Build and operate production AI systems for RAG, evaluation, fine-tuning, serving, and inference optimization.
• Turn prototypes into reusable platform capabilities with CI/CD, evaluation, and governance.
• Architect AWS or GCP environments with Kubernetes, Terraform, and CI/CD for applications and model pipelines.
• Own observability and incident response, and partner on SOC 2/SOX and least-privilege IAM.
• Improve cost visibility and control; optimize GPU usage, inference routing, model selection, and resource sizing.

Skills

Relocation