Software Engineer, AI Agent

Responsibilities

We are the TikTok Monetization - Growth team - building the next-generation AI Agent-powered intelligent growth platform that serves millions of advertisers and reaches billions of users every day. We are embedding LLM reasoning, multimodal perception, and autonomous decision-making directly into the full advertising lifecycle - from ad creation and creative generation to bidding strategy, attribution, and measurement, helping businesses worldwide efficiently connect with customers and achieve commercial success on TikTok.
If you want to ship cutting-edge Agent technology at internet scale with real business impact, this is the place.

What You'll Do
- Architect & build AI Agent systems: Design and build autonomous Agent frameworks for ads growth and marketing scenarios, including but not limited to: Task Planning engines based on ReAct / Plan-and-Execute paradigms, a pluggable Tool-Use & Function Calling skill layer, a Memory management system fusing long-term and short-term memory (vector retrieval + conversation summarization), and a Multi-Agent Orchestration system supporting role-based task delegation and message routing
- Deeply integrate LLM capabilities: Design Prompt Engineering & Chain-of-Thought reasoning pipelines, connect foundation models with business systems via RAG (Retrieval-Augmented Generation) and Structured Output, enabling intelligent decision-making powered by massive advertiser profiles and ad performance data - helping advertisers achieve full-lifecycle growth from Registration → Activation → Scaling
- Build omni-channel personalized marketing Agents: Leveraging an Event-Driven Agent architecture, create AI-driven personalized recommendation and automation marketing solutions spanning WhatsApp, phone, email, ad placements, and more - delivering end-to-end Agentic Workflows (intent recognition → strategy generation → action execution → feedback loop)
- Enhance growth content creation & delivery experience: Leverage multimodal foundation model capabilities, combined with Agent self-evaluation and iterative optimization (Self-Reflection / Critique Loop), to dramatically improve creative asset quality, automated bidding strategy tuning, and overall delivery efficiency
- Collaborate cross-functionally: Work closely with Product, Operations, Sales, and Data Science teams to translate AI capabilities into measurable growth outcomes

Qualifications

Minimum Qualifications:
- MS or above in Computer Science, Artificial Intelligence, or a related field
- 1+ year of software engineering experience in the internet industry, with strong CS fundamentals (data structures, algorithms, OS, networking)
- Deep understanding of AI Agent architectures; hands-on experience with one or more of the following: Agent frameworks (LangChain / LangGraph / AutoGen / CrewAI), Tool-Use & Function Calling mechanisms, RAG pipeline construction (vector databases + Embedding + retrieval strategies), Prompt Engineering (CoT / Few-shot / ReAct Prompting)
- Strong system design skills with the ability to craft sound technical solutions for complex business problems
- Excellent teamwork and communication skills

Preferred Qualifications:
- Experience building ads / recommendation / big-data platforms, having led at least one large-scale project end-to-end
- Experience designing and deploying multi-agent systems (agent communication protocols, state management, fault tolerance, etc.)
- Hands-on MLOps / LLMOps experience - model serving, evaluation, and monitoring pipelines
- Active interest in frontier Agent research: ReAct, Reflexion, Tree-of-Thought, Plan-and-Execute, and beyond
- Open-source contributions or published technical blog posts in the AI/ML space
- Analytical mindset with product sense - able to drive technical decisions from a business perspective

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $162000 - $316800 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates:

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.

Responsibilities

Responsibilities

We are the TikTok Monetization - Growth team - building the next-generation AI Agent-powered intelligent growth platform that serves millions of advertisers and reaches billions of users every day. We are embedding LLM reasoning, multimodal perception, and autonomous decision-making directly into the full advertising lifecycle - from ad creation and creative generation to bidding strategy, attribution, and measurement, helping businesses worldwide efficiently connect with customers and achieve commercial success on TikTok.
If you want to ship cutting-edge Agent technology at internet scale with real business impact, this is the place.

What You'll Do
- Architect & build AI Agent systems: Design and build autonomous Agent frameworks for ads growth and marketing scenarios, including but not limited to: Task Planning engines based on ReAct / Plan-and-Execute paradigms, a pluggable Tool-Use & Function Calling skill layer, a Memory management system fusing long-term and short-term memory (vector retrieval + conversation summarization), and a Multi-Agent Orchestration system supporting role-based task delegation and message routing
- Deeply integrate LLM capabilities: Design Prompt Engineering & Chain-of-Thought reasoning pipelines, connect foundation models with business systems via RAG (Retrieval-Augmented Generation) and Structured Output, enabling intelligent decision-making powered by massive advertiser profiles and ad performance data - helping advertisers achieve full-lifecycle growth from Registration → Activation → Scaling
- Build omni-channel personalized marketing Agents: Leveraging an Event-Driven Agent architecture, create AI-driven personalized recommendation and automation marketing solutions spanning WhatsApp, phone, email, ad placements, and more - delivering end-to-end Agentic Workflows (intent recognition → strategy generation → action execution → feedback loop)
- Enhance growth content creation & delivery experience: Leverage multimodal foundation model capabilities, combined with Agent self-evaluation and iterative optimization (Self-Reflection / Critique Loop), to dramatically improve creative asset quality, automated bidding strategy tuning, and overall delivery efficiency
- Collaborate cross-functionally: Work closely with Product, Operations, Sales, and Data Science teams to translate AI capabilities into measurable growth outcomes

Qualifications

Qualifications

Minimum Qualifications:
- MS or above in Computer Science, Artificial Intelligence, or a related field
- 1+ year of software engineering experience in the internet industry, with strong CS fundamentals (data structures, algorithms, OS, networking)
- Deep understanding of AI Agent architectures; hands-on experience with one or more of the following: Agent frameworks (LangChain / LangGraph / AutoGen / CrewAI), Tool-Use & Function Calling mechanisms, RAG pipeline construction (vector databases + Embedding + retrieval strategies), Prompt Engineering (CoT / Few-shot / ReAct Prompting)
- Strong system design skills with the ability to craft sound technical solutions for complex business problems
- Excellent teamwork and communication skills

Preferred Qualifications:
- Experience building ads / recommendation / big-data platforms, having led at least one large-scale project end-to-end
- Experience designing and deploying multi-agent systems (agent communication protocols, state management, fault tolerance, etc.)
- Hands-on MLOps / LLMOps experience - model serving, evaluation, and monitoring pipelines
- Active interest in frontier Agent research: ReAct, Reflexion, Tree-of-Thought, Plan-and-Execute, and beyond
- Open-source contributions or published technical blog posts in the AI/ML space
- Analytical mindset with product sense - able to drive technical decisions from a business perspective