Senior AI Platform Engineer - Remote, Multi-Tenant SaaS

Caseware; United States; A distancia; USD 150.000 - 190.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Remote work

Prepaid Medicine

Life insurance

Home office stipend

Competitive compensation

100% remote work environment

Training budget

Personal Time Off

Sick Leave Top up

Recognition awards

AI-first environment

Descripción de la vacante

Caseware is seeking an experienced AI platform architect to define and evolve the technical architecture for a cloud-native, multi-tenant AI platform. You will design, build, and operate AI systems using LLMs and retrieval pipelines, ensuring governance, auditability, and scalability across teams.

Lead architectural reviews, pursue PoCs, and mentor engineers while collaborating with product, security, and domain experts.

Formación

• 8+ years of professional software engineering experience.
• 2+ years building and operating production AI systems.
• Experience designing distributed, SaaS, cloud-native, multi-tenant platforms at scale.
• Experience implementing AI guardrails, governance controls, and safety mechanisms.

Responsabilidades

• Define and evolve the technical architecture for Caseware’s AI platform.
• Design, build, and operate AI systems powered by LLMs and related pipelines.
• Design and implement evaluation, governance, auditability, and traceability frameworks.

Conocimientos

Software architecture

Distributed systems

AI platform design

Leadership / mentoring

English communication

Technical leadership

Cloud-native

Herramientas

AWS EKS

AWS Lambda

AWS Bedrock

AWS OpenSearch Serverless

AWS Textract

DynamoDB

S3

LangFuse

LangSmith

GitHub Copilot

GitHub Actions

Nx Monorepo

Jira

Confluence

Microsoft Teams

Outlook

TypeScript

NestJS

Python

Descripción del empleo

Caseware is seeking an experienced AI platform architect to define and evolve the technical architecture for a cloud-native, multi-tenant AI platform. You will design, build, and operate AI systems using LLMs and retrieval pipelines, ensuring governance, auditability, and scalability across teams.

Lead architectural reviews, pursue PoCs, and mentor engineers while collaborating with product, security, and domain experts.