Senior Platform Engineer: AI Infra, Cloud & Observability

BlackCube Labs; United States; A distancia; USD 140.000 - 210.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Medical coverage

Dental coverage

Vision coverage

PTO and holidays

HSA/FSA option

Descripción de la vacante

Vectara is seeking a Senior/Staff Platform Software Engineer to build and scale the core backend infrastructure powering our AI agent platform. You will own design reviews, implement secure services, and drive automation, observability, and reliability at scale.

You’ll collaborate with product, research teams, and DevOps to deploy ML/NLP workloads across multi-cloud environments (GCP/AWS/Azure). Strong Java and Python skills, and hands-on cloud and container experience are essential.

Formación

• 5+ years of backend software engineering experience.
• Proficiency in Java and Python.
• Deep experience with cloud platforms (GCP, AWS, Azure, On-prem).
• Strong containerization and orchestration (Docker, Kubernetes).
• Experience with IaC (Terraform, Pulumi).
• Experience with observability tools (Prometheus, Grafana, ELK/EFK).
• Experience with ML platforms in production.
• Experience designing distributed systems.
• Familiarity with data tooling (Kafka, Spark, Airflow).

Responsabilidades

• Lead code reviews and mentor team members.
• Design and maintain scalable backend services.
• Drive CI/CD, automation, and monitoring pipelines.
• Collaborate with product/research on ML/NLP workloads.
• Improve system reliability and developer experience.
• Contribute to architecture decisions as we scale.
• Champion code quality and DevOps practices.

Conocimientos

Java

Python

GCP

AWS

Azure

Docker

Kubernetes

Terraform

Pulumi

Prometheus

Grafana

ELK

Kafka

Spark

Airflow

Distributed systems

Herramientas

Docker

Kubernetes

Descripción del empleo

Vectara is seeking a Senior/Staff Platform Software Engineer to build and scale the core backend infrastructure powering our AI agent platform. You will own design reviews, implement secure services, and drive automation, observability, and reliability at scale.

You’ll collaborate with product, research teams, and DevOps to deploy ML/NLP workloads across multi-cloud environments (GCP/AWS/Azure). Strong Java and Python skills, and hands-on cloud and container experience are essential.