Senior Software Engineer, Payment AI Platform - USDS

Responsibilities

Team Intro:
We are the TikTok USDS Payment Engineering team. Our mission is to build the one-stop AI-assisted payment platform that allows different TikTok business lines to fully realize the potential of LLM and AI Agents to achieve their goals. We provide a business-centric and user-friendly platform that covers Treasury, Customer Service, Transaction Tools, and Voice of Customer/Business applications. Our vision is maximizing end-to-end AI application development efficiency and ultimately enabling the payment business to achieve self-evolving AI native goal.

Responsibilities:
- Responsible for building an end-to-end payment operation platform, including but not limited to a one-stop operation Workplace covering end-to-end operation processes: a transaction end-to-end configuration center, a customer complaint platform, operation outreach capabilities, page componentization, and back-end open capabilities, etc.
- Responsible for designing scenario-based AI solutions to drive the evolution of operational functions towards online, visual, configurable, rule-based, automated, and intelligent directions, thereby enhancing operational experience and product R&D efficiency.
- Continuously improve and optimize system architecture, constantly enhance system stability and performance, promote the implementation of new technologies in business, and support the high-speed development of payment businesses.
- Have the opportunity to participate in industry research, technology planning, business breakthroughs and other tasks, lead colleagues in the direction to complete requirement delivery, and jointly achieve business goals.
- Partner effectively across various teams, organizations, and internal/external stakeholders to drive complex engineering efforts and align technical strategies.

Qualifications

Minimum Qualifications:
- Bachelor's degree in Computer Science, Engineering, or a related technical discipline.
- 5+ years of hands-on experience building, training, and deploying complex and scalable Software or Machine Learning systems.
- Strong foundation in Computer Science, including algorithms, data structures, and software design patterns. Excellent problem-solving abilities. Have solid programming skills and be familiar with at least one backend development language among Java, PHP, C++, Go, and Python.
- Good system design capabilities, be proficient in distributed system development skills (including MySQL, Redis, MQ, RPC, etc.), and understand their underlying principles and application scenarios.
- Good communication and learning abilities, teamwork skills, problem analysis and solving capabilities, have a strong sense of responsibility and leadership.

Preferred Qualifications:
- Solid programming skills with a strong understanding of Agentic AI and AI platforms like Coze, ChatBot, Rag, A2A protocols, AutoPrompt etc.
- Deep understanding of the full LLM training and serving process.
- Preference will be given to those with experience in operating platforms and B-side R&D.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $187040 - $359720 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).