Lead AI Platform Architect — Enterprise-Scale, Multi-Cloud

Grid Dynamics; Wrocław; On-site; PLN 300,000 - 600,000; Full time

Benefits offered by this job

Medical insurance

Sports benefits

Corporate events

Professional development

Well-equipped office

Job summary

Grid Dynamics seeks a Lead AI Software Engineer to own the technical direction and architecture of a next-generation enterprise AI platform. You will oversee distributed systems, security, and multi-tenant cloud deployments across AWS, Azure, and GCP, guiding an engineering team and partnering with Forward Deployment teams.

You will write Python, work with LangGraph/Tooling, and drive architecture decisions for cost, latency, and compliance while ensuring robust installations in customer clouds.

Qualifications

• 8+ years of commercial software engineering experience in tech lead roles.
• Shipping and operating LLM-based applications at scale and defending against prompt-injections.
• Deep multi-tenant SaaS architecture and cloud deployment across AWS/Azure/GCP.

Responsibilities

• Lead and mentor a team of senior engineers and set technical standards.
• Own end-to-end platform architecture for enterprise AI platform.
• Design data isolation, identity, and access for single-tenant/cloud installs and multi-tenant offerings.
• Lead hands-on engineering on distributed systems, performance under load, and security.
• Collaborate with product leadership to translate roadmaps into engineering commitments.

Skills

Leadership

Architectural design

Distributed systems

Python

TypeScript/Node.js

PostgreSQL

Cloud (AWS)

Tools

LangGraph

Cerbos

WorkOS

Job description

Grid Dynamics seeks a Lead AI Software Engineer to own the technical direction and architecture of a next-generation enterprise AI platform. You will oversee distributed systems, security, and multi-tenant cloud deployments across AWS, Azure, and GCP, guiding an engineering team and partnering with Forward Deployment teams.

You will write Python, work with LangGraph/Tooling, and drive architecture decisions for cost, latency, and compliance while ensuring robust installations in customer clouds.