Enterprise AI Platform Architect

ByteDance; New York (NY); On-site; USD 218,000 - 480,000; Full time

Job summary

ByteDance is seeking an architect-level contributor to lead the design, development, and adoption of enterprise AI agent capabilities, AI harness platforms, and RAG-based knowledge bases across the organization.

This role requires deep technical architecture expertise, hands-on AI platform experience, and product management capabilities to drive enterprise-wide adoption and ensure scalable, secure AI offerings.

Qualifications

• BS degree in Computer Science, similar technical field of study or equivalent practical experience.
• 5+ years software development experience preferably with Golang or Python.
• Experience driving enterprise AI adoption across multiple business units or internal product teams.
• Prior experience combining architect-level technical ownership with product management responsibilities.
• Strong understanding of AI system tradeoffs, including cost, latency, accuracy, reliability, safety, and user experience.

Responsibilities

• Lead design and adoption of enterprise AI agent platforms and AI harness capabilities.
• Define architecture roadmap for AI agent platforms, orchestration, tool integration, and governance.
• Partner with product, engineering, data, security, and business teams to identify high-value AI use cases and drive production.
• Establish architecture principles, design patterns, and best practices for enterprise AI platforms.
• Provide technical leadership on reliability, observability, cost optimization, privacy, and responsible AI practices.
• Apply product management thinking to define platform vision, adoption metrics, and rollout plans.

Skills

Architect-level ownership

Golang

Python

Product management

Enterprise AI adoption

Education

BS in Computer Science or equivalent

Job description

ByteDance is seeking an architect-level contributor to lead the design, development, and adoption of enterprise AI agent capabilities, AI harness platforms, and RAG-based knowledge bases across the organization.

This role requires deep technical architecture expertise, hands-on AI platform experience, and product management capabilities to drive enterprise-wide adoption and ensure scalable, secure AI offerings.