AI & Security Process Engineer - USDS

Responsibilities

• Design and Develop AI Agents:
  Architect, build, and deploy robust, multi-step AI agents capable of complex reasoning, tool use, and decision-making using frameworks like Lang Chain, Auto Gen, or CrewAI. Develop and integrate agentic systems—using LLMs, RAG, and tool-use/function-calling frameworks—to automate or accelerate complex tasks for end-users.
• RAG:
  Deep, practical experience with the end-to-end RAG lifecycle, from designing chunking and hybrid retrieval strategies for domain-specific data to implementing agentic design patterns.
• Workflow and Process Design:
  Translate user needs into robust, autonomous workflows that can reason, plan, and execute actions.
• Integrate Tools and Data Sources:
  Equip agents with the ability to interact with external systems by integrating APIs, databases, and other data sources to enable real-world action and information retrieval.
• Implement Agentic Architectures:
  Develop and implement advanced agentic patterns such as ReAct (Reasoning and Acting), plan-and-execute, and multi-agent collaboration to solve complex, open-ended problems.
  
  Optimize and Evaluate Performance:
  Establish rigorous metrics to evaluate agent performance, reliability, and efficiency. Continuously iterate on agent design, prompting strategies, and model choice to improve outcomes.
• LLM Customization:
  Fine-tune and adapt foundational LLMs to enhance their capabilities for specific agentic tasks and domains. Implement and refine Retrieval‑Augmented Generation (RAG) pipelines to provide agents with relevant, up-to-date context. Proven experience building and shipping applications powered by Large Language Models (LLMs).
• Collaboration:
  
  Work closely with product managers, data scientists, and other engineers to define requirements, identify opportunities for automation, and integrate agentic solutions into our core products and internal workflows.
• Stay Current:
  Keep up-to-date with the latest advancements in agentic AI, LLMs, and autonomous systems, and champion the adoption of new techniques and technologies within the team.

• Experience designing and building multi‑agent systems where agents collaborate or compete.
• Published research in top‑tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR).
• Experience with MLOps practices and tools (e.g., Docker, Kubernetes, CI/CD pipelines) for deploying and monitoring AI systems.
• A strong passion for the potential of autonomous agents and a creative mindset for finding novel applications.
• Experience building automated tools in Java, C or Power Shell as well as Experience with SQL or other query languages.

Tik Tok is the leading destination for short‑form mobile video. Our mission is to inspire creativity and bring joy. U.S. Data Security (“USDS”) is a subsidiary of Tik Tok in the U.S. This new, security‑first division was created to bring heightened focus and governance to our data protection policies and content assurance protocols to keep U.S. users safe. Our focus is on providing oversight and protection of the Tik Tok platform and U.S. user data, so millions of Americans can continue turning to Tik Tok to learn something new, earn a living, express themselves creatively, or be entertained.

The teams within USDS that deliver on this commitment daily…