Solutions Engineer, Partnerships & Ads (AI-Driven)

TikTok; New York (NY); On-site; USD 162,000 - 317,000; Full time

Job summary

TikTok is building out its Solutions Engineering team to help our external clients thrive on this journey. As a Solutions Engineer, you will architect and build solutions, prioritizing client success and cross-functional collaboration to meet business objectives.

Focus areas include applying AI: deploying, scaling models, building RAG pipelines, and designing systems that ground LLMs in enterprise data. Expect to engage with API capabilities and partner integrations across marketing tech.

Qualifications

• Bachelor's degree in Computer Science or related field.
• 3+ years of experience shipping production-grade code.
• Experience building or shipping ML/LLM-powered products.
• Experience with model evaluation, fine-tuning, or prompt design.
• Proficiency in Python, Go, Java, or C/C++.
• Able to explain technical concepts to non-technical audiences.
• Strong knowledge of API and backend systems design.

Responsibilities

• Develop and maintain relationships with key strategic partners and agencies.
• Collaborate cross-functionally with Partnerships and Product teams on technical integrations.
• Be an expert on TikTok API capabilities and partner offerings from a technical lens.
• Advocate for API improvements and influence product roadmap with internal teams.
• Build and ship new products and end-to-end integrations with Ads product engineering teams.
• Maintain subject matter expertise on marketing technology and API trends.

Skills

Production code

ML/LLM experience

Prompt design

API design

Cross-functional communication

Python

Go

Java

C/C++

Education

Bachelor's degree in Computer Science

Tools

REST APIs

Job description

TikTok is building out its Solutions Engineering team to help our external clients thrive on this journey. As a Solutions Engineer, you will architect and build solutions, prioritizing client success and cross-functional collaboration to meet business objectives.

Focus areas include applying AI: deploying, scaling models, building RAG pipelines, and designing systems that ground LLMs in enterprise data. Expect to engage with API capabilities and partner integrations across marketing tech.